From b3a639a8e8347bc29c15abe54c73ae5d890379ff Mon Sep 17 00:00:00 2001
From: benjas <909336740@qq.com>
Date: Sun, 22 Aug 2021 14:02:08 +0800
Subject: [PATCH] Add. Stacking better than Blending and linear-weighted

---
 .../Stacking-checkpoint.ipynb                 | 727 ++++++++++++++----
 竞赛优胜技巧/Stacking.ipynb             | 727 ++++++++++++++----
 2 files changed, 1112 insertions(+), 342 deletions(-)

diff --git a/竞赛优胜技巧/.ipynb_checkpoints/Stacking-checkpoint.ipynb b/竞赛优胜技巧/.ipynb_checkpoints/Stacking-checkpoint.ipynb
index ef7f238..4ae86fe 100644
--- a/竞赛优胜技巧/.ipynb_checkpoints/Stacking-checkpoint.ipynb
+++ b/竞赛优胜技巧/.ipynb_checkpoints/Stacking-checkpoint.ipynb
@@ -13,7 +13,7 @@
    "id": "0b365a02",
    "metadata": {},
    "source": [
-    "## 先说结论，该数据集（fetch_covtype）Stacking的方法比线性加权更好\n",
+    "## 先说结论，该数据集（fetch_covtype）Stacking的方法相比Blending和线性加权更好\n",
     "比赛中我们常用线性加权作为最终的融合方式，我们同样也会好奇怎样的线性加权权重更好，下面也会举例子\n",
     "参考：https://github.com/rushter/heamy/tree/master/examples"
    ]
@@ -67,7 +67,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 1,
    "id": "69632c6a",
    "metadata": {},
    "outputs": [
@@ -86,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 2,
    "id": "ca421279",
    "metadata": {},
    "outputs": [],
@@ -119,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 3,
    "id": "9a0fabe1",
    "metadata": {},
    "outputs": [],
@@ -130,7 +130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 6,
    "id": "5bd75178",
    "metadata": {},
    "outputs": [
@@ -153,14 +153,14 @@
     "print(y)\n",
     "ord = OrdinalEncoder()\n",
     "y = ord.fit_transform(y.reshape(-1, 1))\n",
-    "y = y_enc.reshape(-1, )\n",
+    "y = y.reshape(-1, )\n",
     "print('七分类任务，处理后：',np.unique(y))\n",
     "print(y)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 7,
    "id": "23d9778c",
    "metadata": {},
    "outputs": [
@@ -182,7 +182,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 8,
    "id": "eac48668",
    "metadata": {},
    "outputs": [
@@ -204,7 +204,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 9,
    "id": "fba3f975",
    "metadata": {},
    "outputs": [
@@ -226,7 +226,7 @@
        "        0.000e+00]])"
       ]
      },
-     "execution_count": 50,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -246,7 +246,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 10,
    "id": "e8393e73",
    "metadata": {},
    "outputs": [],
@@ -293,7 +293,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 11,
    "id": "78ab0083",
    "metadata": {},
    "outputs": [],
@@ -313,7 +313,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 13,
    "id": "173ef0f0",
    "metadata": {},
    "outputs": [
@@ -321,185 +321,485 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Best Score (log_loss): 0.18744137777851164\n",
-      "Best Weights: [0.36556831 0.00303401 0.63139768]\n"
+      "Best Score (log_loss): 0.18646435443714865\n",
+      "Best Weights: [2.53464919e-01 1.48562205e-20 7.46535081e-01]\n",
+      "Wall time: 14min 19s\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "array([0.36556831, 0.00303401, 0.63139768])"
+       "array([2.53464919e-01, 1.48562205e-20, 7.46535081e-01])"
       ]
      },
-     "execution_count": 53,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "pipeline.find_weights(scorer=log_loss, )  # 输出最优权重组合"
+    "%%time\n",
+    "pipeline.find_weights(scorer=log_loss)  # 输出最优权重组合"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 22,
    "id": "80726d19",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wall time: 1h 39min 20s\n"
+     ]
+    }
+   ],
    "source": [
+    "%%time\n",
     "# 5折训练构建5折模型特征集，这里比较耗时\n",
-    "stack_ds = pipeline.stack(k=5,stratify=False,seed=42,full_test=False)  # full_test指明预测全部还是预测当前折的验证集"
+    "stack_ds = pipeline.stack(k=5,seed=42)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 26,
    "id": "b25bba3c",
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "           xgb_0     xgb_1         xgb_2         xgb_3         xgb_4  \\\n",
-      "0       0.177179  0.818728  2.185222e-07  9.264143e-09  4.090067e-03   \n",
-      "1       0.005155  0.994845  7.055579e-10  1.326343e-08  6.331572e-09   \n",
-      "2       0.293492  0.706508  3.650662e-10  1.017633e-09  8.823530e-09   \n",
-      "3       0.478112  0.521816  3.207779e-06  2.878019e-08  1.076500e-08   \n",
-      "4       0.992430  0.006652  1.233117e-05  1.887496e-07  1.569583e-06   \n",
-      "...          ...       ...           ...           ...           ...   \n",
-      "435754  0.988518  0.011477  3.190797e-09  5.645121e-08  2.940739e-09   \n",
-      "435755  0.969212  0.030723  2.142020e-08  1.572054e-05  4.321913e-07   \n",
-      "435756  0.415850  0.584142  4.283793e-08  7.367601e-08  6.148067e-07   \n",
-      "435757  0.602601  0.397399  6.606462e-10  1.015894e-09  7.221973e-08   \n",
-      "435758  0.834587  0.165411  3.267833e-09  2.057172e-08  2.078704e-08   \n",
-      "\n",
-      "               xgb_5         xgb_6     lgb_0     lgb_1          lgb_2  ...  \\\n",
-      "0       1.725062e-06  1.048052e-06  0.172406  0.812678   1.416886e-06  ...   \n",
-      "1       1.435787e-09  1.603579e-10  0.008114  0.991886   0.000000e+00  ...   \n",
-      "2       6.384080e-10  2.823794e-08  0.817627  0.182372   0.000000e+00  ...   \n",
-      "3       2.230641e-06  6.630235e-05  0.465733  0.534184   0.000000e+00  ...   \n",
-      "4       5.604260e-07  9.037877e-04  0.932050  0.043451   0.000000e+00  ...   \n",
-      "...              ...           ...       ...       ...            ...  ...   \n",
-      "435754  1.530261e-08  4.466830e-06  0.970593  0.029399   0.000000e+00  ...   \n",
-      "435755  5.574208e-10  4.977021e-05  0.862591  0.136644   0.000000e+00  ...   \n",
-      "435756  2.371389e-06  5.185283e-06  0.466886  0.533039   0.000000e+00  ...   \n",
-      "435757  2.326313e-09  9.193871e-09  0.674250  0.325750  4.092880e-211  ...   \n",
-      "435758  5.976972e-08  2.204258e-06  0.709320  0.290680   0.000000e+00  ...   \n",
-      "\n",
-      "               lgb_4         lgb_5         lgb_6  rf_0  rf_1  rf_2  rf_3  \\\n",
-      "0       1.486358e-02  5.093522e-05  6.805300e-08  0.06  0.92   0.0   0.0   \n",
-      "1       0.000000e+00  0.000000e+00  0.000000e+00  0.12  0.88   0.0   0.0   \n",
-      "2       4.452850e-07  7.825338e-09  1.012052e-07  0.63  0.37   0.0   0.0   \n",
-      "3       0.000000e+00  0.000000e+00  8.245405e-05  0.56  0.44   0.0   0.0   \n",
-      "4       0.000000e+00  0.000000e+00  2.449972e-02  0.95  0.04   0.0   0.0   \n",
-      "...              ...           ...           ...   ...   ...   ...   ...   \n",
-      "435754  0.000000e+00  0.000000e+00  7.871809e-06  0.97  0.03   0.0   0.0   \n",
-      "435755  0.000000e+00  0.000000e+00  7.647430e-04  0.93  0.06   0.0   0.0   \n",
-      "435756  0.000000e+00  0.000000e+00  7.493861e-05  0.45  0.55   0.0   0.0   \n",
-      "435757  0.000000e+00  0.000000e+00  0.000000e+00  0.52  0.48   0.0   0.0   \n",
-      "435758  0.000000e+00  0.000000e+00  0.000000e+00  0.87  0.13   0.0   0.0   \n",
-      "\n",
-      "        rf_4  rf_5  rf_6  \n",
-      "0       0.02   0.0  0.00  \n",
-      "1       0.00   0.0  0.00  \n",
-      "2       0.00   0.0  0.00  \n",
-      "3       0.00   0.0  0.00  \n",
-      "4       0.00   0.0  0.01  \n",
-      "...      ...   ...   ...  \n",
-      "435754  0.00   0.0  0.00  \n",
-      "435755  0.00   0.0  0.01  \n",
-      "435756  0.00   0.0  0.00  \n",
-      "435757  0.00   0.0  0.00  \n",
-      "435758  0.00   0.0  0.00  \n",
-      "\n",
-      "[435759 rows x 21 columns]\n"
-     ]
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>xgb_0</th>\n",
+       "      <th>xgb_1</th>\n",
+       "      <th>xgb_2</th>\n",
+       "      <th>xgb_3</th>\n",
+       "      <th>xgb_4</th>\n",
+       "      <th>xgb_5</th>\n",
+       "      <th>xgb_6</th>\n",
+       "      <th>lgb_0</th>\n",
+       "      <th>lgb_1</th>\n",
+       "      <th>lgb_2</th>\n",
+       "      <th>...</th>\n",
+       "      <th>lgb_4</th>\n",
+       "      <th>lgb_5</th>\n",
+       "      <th>lgb_6</th>\n",
+       "      <th>rf_0</th>\n",
+       "      <th>rf_1</th>\n",
+       "      <th>rf_2</th>\n",
+       "      <th>rf_3</th>\n",
+       "      <th>rf_4</th>\n",
+       "      <th>rf_5</th>\n",
+       "      <th>rf_6</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.177179</td>\n",
+       "      <td>0.818728</td>\n",
+       "      <td>2.185222e-07</td>\n",
+       "      <td>9.264143e-09</td>\n",
+       "      <td>4.090067e-03</td>\n",
+       "      <td>1.725062e-06</td>\n",
+       "      <td>1.048052e-06</td>\n",
+       "      <td>0.179625</td>\n",
+       "      <td>0.804684</td>\n",
+       "      <td>0.000003</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.562435e-02</td>\n",
+       "      <td>6.370849e-05</td>\n",
+       "      <td>1.004259e-08</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.96</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.005155</td>\n",
+       "      <td>0.994845</td>\n",
+       "      <td>7.055579e-10</td>\n",
+       "      <td>1.326343e-08</td>\n",
+       "      <td>6.331572e-09</td>\n",
+       "      <td>1.435787e-09</td>\n",
+       "      <td>1.603579e-10</td>\n",
+       "      <td>0.008114</td>\n",
+       "      <td>0.991886</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>0.87</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.293492</td>\n",
+       "      <td>0.706508</td>\n",
+       "      <td>3.650662e-10</td>\n",
+       "      <td>1.017633e-09</td>\n",
+       "      <td>8.823530e-09</td>\n",
+       "      <td>6.384080e-10</td>\n",
+       "      <td>2.823794e-08</td>\n",
+       "      <td>0.831445</td>\n",
+       "      <td>0.168555</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.999034e-07</td>\n",
+       "      <td>4.015190e-09</td>\n",
+       "      <td>4.997854e-09</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>0.37</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.478112</td>\n",
+       "      <td>0.521816</td>\n",
+       "      <td>3.207779e-06</td>\n",
+       "      <td>2.878019e-08</td>\n",
+       "      <td>1.076500e-08</td>\n",
+       "      <td>2.230641e-06</td>\n",
+       "      <td>6.630235e-05</td>\n",
+       "      <td>0.465733</td>\n",
+       "      <td>0.534184</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>8.245405e-05</td>\n",
+       "      <td>0.55</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.992430</td>\n",
+       "      <td>0.006652</td>\n",
+       "      <td>1.233117e-05</td>\n",
+       "      <td>1.887496e-07</td>\n",
+       "      <td>1.569583e-06</td>\n",
+       "      <td>5.604260e-07</td>\n",
+       "      <td>9.037877e-04</td>\n",
+       "      <td>0.932050</td>\n",
+       "      <td>0.043451</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>2.449972e-02</td>\n",
+       "      <td>0.97</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      xgb_0     xgb_1         xgb_2         xgb_3         xgb_4         xgb_5  \\\n",
+       "0  0.177179  0.818728  2.185222e-07  9.264143e-09  4.090067e-03  1.725062e-06   \n",
+       "1  0.005155  0.994845  7.055579e-10  1.326343e-08  6.331572e-09  1.435787e-09   \n",
+       "2  0.293492  0.706508  3.650662e-10  1.017633e-09  8.823530e-09  6.384080e-10   \n",
+       "3  0.478112  0.521816  3.207779e-06  2.878019e-08  1.076500e-08  2.230641e-06   \n",
+       "4  0.992430  0.006652  1.233117e-05  1.887496e-07  1.569583e-06  5.604260e-07   \n",
+       "\n",
+       "          xgb_6     lgb_0     lgb_1     lgb_2  ...         lgb_4  \\\n",
+       "0  1.048052e-06  0.179625  0.804684  0.000003  ...  1.562435e-02   \n",
+       "1  1.603579e-10  0.008114  0.991886  0.000000  ...  0.000000e+00   \n",
+       "2  2.823794e-08  0.831445  0.168555  0.000000  ...  4.999034e-07   \n",
+       "3  6.630235e-05  0.465733  0.534184  0.000000  ...  0.000000e+00   \n",
+       "4  9.037877e-04  0.932050  0.043451  0.000000  ...  0.000000e+00   \n",
+       "\n",
+       "          lgb_5         lgb_6  rf_0  rf_1  rf_2  rf_3  rf_4  rf_5  rf_6  \n",
+       "0  6.370849e-05  1.004259e-08  0.03  0.96   0.0   0.0  0.01   0.0   0.0  \n",
+       "1  0.000000e+00  0.000000e+00  0.13  0.87   0.0   0.0  0.00   0.0   0.0  \n",
+       "2  4.015190e-09  4.997854e-09  0.63  0.37   0.0   0.0  0.00   0.0   0.0  \n",
+       "3  0.000000e+00  8.245405e-05  0.55  0.45   0.0   0.0  0.00   0.0   0.0  \n",
+       "4  0.000000e+00  2.449972e-02  0.97  0.03   0.0   0.0  0.00   0.0   0.0  \n",
+       "\n",
+       "[5 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
     "# 模型输出的训练集，7个特征对应7个标签的预测概率\n",
-    "print(stack_ds.X_train)"
+    "stack_ds.X_train.head()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 28,
    "id": "835205e9",
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "               xgb_0     xgb_1         xgb_2         xgb_3         xgb_4  \\\n",
-      "0       9.876224e-01  0.000789  2.774616e-06  4.129093e-07  1.311387e-06   \n",
-      "1       5.139124e-02  0.929659  1.852793e-03  1.518293e-07  1.692924e-02   \n",
-      "2       7.695035e-04  0.973729  6.878623e-04  1.573823e-07  2.408167e-02   \n",
-      "3       3.376913e-02  0.966229  2.024872e-07  7.321523e-08  1.071163e-06   \n",
-      "4       1.013981e-03  0.998553  3.794874e-06  8.755425e-08  4.243054e-04   \n",
-      "...              ...       ...           ...           ...           ...   \n",
-      "145248  9.615189e-01  0.038480  6.486028e-08  1.744931e-08  1.069370e-06   \n",
-      "145249  3.055384e-02  0.969440  2.475371e-07  5.530033e-08  4.299908e-06   \n",
-      "145250  8.224608e-06  0.058361  9.212288e-01  9.705171e-08  5.440121e-05   \n",
-      "145251  9.183387e-01  0.081601  5.612090e-08  1.088283e-08  5.225256e-07   \n",
-      "145252  9.203915e-07  0.003578  2.372825e-01  1.582836e-06  3.307252e-07   \n",
-      "\n",
-      "               xgb_5         xgb_6     lgb_0     lgb_1         lgb_2  ...  \\\n",
-      "0       7.851924e-09  1.158422e-02  0.962538  0.004222  9.599869e-23  ...   \n",
-      "1       1.613036e-04  6.763449e-06  0.070947  0.882463  2.232464e-03  ...   \n",
-      "2       7.296442e-04  1.884172e-06  0.004029  0.945838  1.014722e-02  ...   \n",
-      "3       7.227585e-08  1.448203e-09  0.066538  0.933450  1.206630e-06  ...   \n",
-      "4       4.374311e-06  4.566837e-09  0.001334  0.997391  1.580417e-06  ...   \n",
-      "...              ...           ...       ...       ...           ...  ...   \n",
-      "145248  5.049759e-08  4.010809e-07  0.917842  0.082153  2.154302e-17  ...   \n",
-      "145249  1.255851e-08  1.224208e-06  0.058622  0.941370  1.332795e-12  ...   \n",
-      "145250  2.034389e-02  3.132630e-06  0.000268  0.083680  8.789707e-01  ...   \n",
-      "145251  2.566383e-07  5.976933e-05  0.875834  0.123030  2.631276e-12  ...   \n",
-      "145252  7.591362e-01  6.988637e-08  0.000032  0.037757  2.462795e-01  ...   \n",
-      "\n",
-      "                lgb_4         lgb_5          lgb_6   rf_0   rf_1   rf_2  rf_3  \\\n",
-      "0       1.726260e-240  0.000000e+00   3.324009e-02  0.984  0.000  0.000   0.0   \n",
-      "1        4.396802e-02  3.888647e-04   1.077146e-08  0.106  0.816  0.038   0.0   \n",
-      "2        3.329283e-02  6.693269e-03   3.213404e-09  0.008  0.950  0.002   0.0   \n",
-      "3        9.908823e-06  1.371448e-07   1.280235e-09  0.078  0.922  0.000   0.0   \n",
-      "4        1.273086e-03  7.811306e-07   5.594472e-10  0.004  0.988  0.000   0.0   \n",
-      "...               ...           ...            ...    ...    ...    ...   ...   \n",
-      "145248   6.191352e-08  0.000000e+00   4.958509e-06  0.968  0.032  0.000   0.0   \n",
-      "145249   7.656931e-06  3.415083e-47   2.271880e-07  0.018  0.972  0.000   0.0   \n",
-      "145250   2.052535e-04  3.687570e-02   1.393421e-09  0.000  0.040  0.946   0.0   \n",
-      "145251   2.521124e-07  5.749375e-08   1.135236e-03  0.992  0.008  0.000   0.0   \n",
-      "145252   2.927400e-06  7.159244e-01  8.608624e-140  0.000  0.018  0.110   0.0   \n",
-      "\n",
-      "         rf_4   rf_5   rf_6  \n",
-      "0       0.000  0.000  0.016  \n",
-      "1       0.034  0.006  0.000  \n",
-      "2       0.032  0.008  0.000  \n",
-      "3       0.000  0.000  0.000  \n",
-      "4       0.008  0.000  0.000  \n",
-      "...       ...    ...    ...  \n",
-      "145248  0.000  0.000  0.000  \n",
-      "145249  0.010  0.000  0.000  \n",
-      "145250  0.000  0.014  0.000  \n",
-      "145251  0.000  0.000  0.000  \n",
-      "145252  0.000  0.872  0.000  \n",
-      "\n",
-      "[145253 rows x 21 columns]\n"
-     ]
+     "data": {
+      "text/html": [
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+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>xgb_0</th>\n",
+       "      <th>xgb_1</th>\n",
+       "      <th>xgb_2</th>\n",
+       "      <th>xgb_3</th>\n",
+       "      <th>xgb_4</th>\n",
+       "      <th>xgb_5</th>\n",
+       "      <th>xgb_6</th>\n",
+       "      <th>lgb_0</th>\n",
+       "      <th>lgb_1</th>\n",
+       "      <th>lgb_2</th>\n",
+       "      <th>...</th>\n",
+       "      <th>lgb_4</th>\n",
+       "      <th>lgb_5</th>\n",
+       "      <th>lgb_6</th>\n",
+       "      <th>rf_0</th>\n",
+       "      <th>rf_1</th>\n",
+       "      <th>rf_2</th>\n",
+       "      <th>rf_3</th>\n",
+       "      <th>rf_4</th>\n",
+       "      <th>rf_5</th>\n",
+       "      <th>rf_6</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.991493</td>\n",
+       "      <td>0.000210</td>\n",
+       "      <td>4.796058e-06</td>\n",
+       "      <td>6.178684e-08</td>\n",
+       "      <td>6.947614e-07</td>\n",
+       "      <td>2.410490e-09</td>\n",
+       "      <td>8.291459e-03</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>0.99</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.024731</td>\n",
+       "      <td>0.964372</td>\n",
+       "      <td>6.387765e-04</td>\n",
+       "      <td>4.205048e-08</td>\n",
+       "      <td>1.006575e-02</td>\n",
+       "      <td>1.879628e-04</td>\n",
+       "      <td>4.830114e-06</td>\n",
+       "      <td>0.065073</td>\n",
+       "      <td>0.877354</td>\n",
+       "      <td>0.001678</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5.530599e-02</td>\n",
+       "      <td>0.000589</td>\n",
+       "      <td>8.601484e-11</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.000780</td>\n",
+       "      <td>0.979776</td>\n",
+       "      <td>8.593459e-04</td>\n",
+       "      <td>1.267791e-07</td>\n",
+       "      <td>1.710379e-02</td>\n",
+       "      <td>1.477527e-03</td>\n",
+       "      <td>2.521008e-06</td>\n",
+       "      <td>0.005164</td>\n",
+       "      <td>0.933849</td>\n",
+       "      <td>0.016355</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.657553e-02</td>\n",
+       "      <td>0.008057</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.97</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.042695</td>\n",
+       "      <td>0.957304</td>\n",
+       "      <td>2.283268e-08</td>\n",
+       "      <td>4.387427e-08</td>\n",
+       "      <td>4.175481e-07</td>\n",
+       "      <td>4.406019e-08</td>\n",
+       "      <td>6.909629e-10</td>\n",
+       "      <td>0.054392</td>\n",
+       "      <td>0.945608</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.285638e-08</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.96</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.000457</td>\n",
+       "      <td>0.999334</td>\n",
+       "      <td>3.366338e-06</td>\n",
+       "      <td>4.893879e-08</td>\n",
+       "      <td>2.045808e-04</td>\n",
+       "      <td>7.889498e-07</td>\n",
+       "      <td>1.415576e-09</td>\n",
+       "      <td>0.001367</td>\n",
+       "      <td>0.995857</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.776106e-03</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.99</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      xgb_0     xgb_1         xgb_2         xgb_3         xgb_4         xgb_5  \\\n",
+       "0  0.991493  0.000210  4.796058e-06  6.178684e-08  6.947614e-07  2.410490e-09   \n",
+       "1  0.024731  0.964372  6.387765e-04  4.205048e-08  1.006575e-02  1.879628e-04   \n",
+       "2  0.000780  0.979776  8.593459e-04  1.267791e-07  1.710379e-02  1.477527e-03   \n",
+       "3  0.042695  0.957304  2.283268e-08  4.387427e-08  4.175481e-07  4.406019e-08   \n",
+       "4  0.000457  0.999334  3.366338e-06  4.893879e-08  2.045808e-04  7.889498e-07   \n",
+       "\n",
+       "          xgb_6     lgb_0     lgb_1     lgb_2  ...         lgb_4     lgb_5  \\\n",
+       "0  8.291459e-03  0.000000  0.000000  0.000000  ...  0.000000e+00  0.000000   \n",
+       "1  4.830114e-06  0.065073  0.877354  0.001678  ...  5.530599e-02  0.000589   \n",
+       "2  2.521008e-06  0.005164  0.933849  0.016355  ...  3.657553e-02  0.008057   \n",
+       "3  6.909629e-10  0.054392  0.945608  0.000000  ...  4.285638e-08  0.000000   \n",
+       "4  1.415576e-09  0.001367  0.995857  0.000000  ...  2.776106e-03  0.000000   \n",
+       "\n",
+       "          lgb_6  rf_0  rf_1  rf_2  rf_3  rf_4  rf_5  rf_6  \n",
+       "0  1.000000e+00  0.99  0.00  0.00   0.0  0.00  0.00  0.01  \n",
+       "1  8.601484e-11  0.09  0.80  0.05   0.0  0.06  0.00  0.00  \n",
+       "2  0.000000e+00  0.01  0.97  0.00   0.0  0.01  0.01  0.00  \n",
+       "3  0.000000e+00  0.04  0.96  0.00   0.0  0.00  0.00  0.00  \n",
+       "4  0.000000e+00  0.00  0.99  0.00   0.0  0.01  0.00  0.00  \n",
+       "\n",
+       "[5 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
     "# 模型输出的测试集，7个特征对应7个标签的预测概率\n",
-    "print(stack_ds.X_test) "
+    "stack_ds.X_test.head()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 30,
    "id": "b9db35dc",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wall time: 1min 53s\n"
+     ]
+    }
+   ],
    "source": [
+    "%%time\n",
     "# 用lr做最后一层\n",
     "stacker = Classifier(dataset=stack_ds, estimator=LogisticRegression, parameters={\"solver\": 'lbfgs', \"max_iter\": 1000},use_cache=False)\n",
     "predict_stack = stacker.predict()"
@@ -507,7 +807,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 32,
    "id": "a4a48219",
    "metadata": {},
    "outputs": [
@@ -515,19 +815,19 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[9.95173402e-01 2.67623709e-03 4.23846755e-08 ... 3.15435935e-05\n",
-      "  5.66194220e-06 2.11044140e-03]\n",
-      " [2.23612439e-02 9.70927685e-01 1.23929922e-03 ... 4.49727904e-03\n",
-      "  8.73983383e-04 9.97020226e-05]\n",
-      " [6.22588197e-03 9.89402233e-01 9.81655972e-04 ... 2.83331258e-03\n",
-      "  5.22139184e-04 3.45071569e-05]\n",
+      "[[9.99137967e-01 4.76574513e-04 3.32764186e-07 ... 3.03237700e-06\n",
+      "  1.62161211e-06 3.79326620e-04]\n",
+      " [2.00732175e-02 9.71682830e-01 1.51484266e-03 ... 5.69138554e-03\n",
+      "  9.40725428e-04 9.60822625e-05]\n",
+      " [5.54556002e-03 9.91048437e-01 8.04840682e-04 ... 2.11437934e-03\n",
+      "  4.56463787e-04 3.00919502e-05]\n",
       " ...\n",
-      " [5.36335125e-06 2.06267200e-03 9.90604140e-01 ... 8.55252386e-04\n",
-      "  4.18405061e-03 1.64678945e-05]\n",
-      " [9.96602824e-01 2.15991442e-03 7.27481581e-08 ... 3.63552051e-05\n",
-      "  6.80942632e-06 1.19199377e-03]\n",
-      " [5.89156494e-05 1.15333400e-03 1.09178439e-02 ... 3.09244417e-04\n",
-      "  9.85167196e-01 2.21261408e-05]]\n"
+      " [4.60179790e-06 1.78298095e-03 9.91553958e-01 ... 7.26752933e-04\n",
+      "  3.79135124e-03 1.53584401e-05]\n",
+      " [9.96307096e-01 2.43558944e-03 1.01596361e-07 ... 3.94985596e-05\n",
+      "  7.41569805e-06 1.20819024e-03]\n",
+      " [5.34671504e-05 7.62534718e-04 5.58323657e-03 ... 2.11410908e-04\n",
+      "  9.91805379e-01 1.69502656e-05]]\n"
      ]
     }
    ],
@@ -553,7 +853,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 33,
    "id": "a28806a0",
    "metadata": {},
    "outputs": [
@@ -561,9 +861,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.9284696357390209\n",
-      "0.8890005714167694\n",
-      "0.9511404239499356\n"
+      "0.9254473229468583\n",
+      "0.8412562907478676\n",
+      "0.9535087055000585\n"
      ]
     }
    ],
@@ -573,6 +873,28 @@
     "print(accuracy_score(np.argmax(stack_ds.X_test.iloc[:, 14:].values, axis=1),y_test))  # RF"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "1db92fec",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.9537840870756542\n",
+      "Wall time: 50.8 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# 测试单模运行结果是否一致\n",
+    "rf_predict = rf_model(X_train, y_train, X_test, None)\n",
+    "print(accuracy_score(np.argmax(rf_predict, axis=1),y_test))  # RF"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "2e9423ce",
@@ -583,7 +905,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 37,
    "id": "d2b50ba4",
    "metadata": {},
    "outputs": [
@@ -591,8 +913,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "主观根据结果blending： 0.9425209806337908\n",
-      "根据最优权重的blending： 0.9488616414118813\n"
+      "主观根据结果blending： 0.9504106627746071\n",
+      "根据最优权重的线性加权： 0.9530749795184953\n"
      ]
     }
    ],
@@ -603,19 +925,74 @@
     "rf_t = stack_ds.X_test.iloc[:, 14:].values\n",
     "\n",
     "# 根据分数好坏随机定\n",
-    "result = 0.3*xgb_t+0.2*lgb_t+0.5*rf_t\n",
+    "result = 0.2*xgb_t+0.1*lgb_t+0.7*rf_t\n",
     "print('主观根据结果blending：', accuracy_score(np.argmax(result, axis=1), y_test))\n",
-    "# 根据上面提供的最优权重 Best Weights: [0.36556831 0.00303401 0.63139768]\n",
-    "result =  0.36556831*xgb_t+0.00303401*lgb_t+0.63139768*rf_t\n",
-    "print('根据最优权重的blending：',accuracy_score(np.argmax(result, axis=1), y_test))"
+    "# 根据上面提供的最优权重 Best Weights: [2.53464919e-01 1.48562205e-20 7.46535081e-01]\n",
+    "result =  2.53464919e-01*xgb_t+1.48562205e-20*lgb_t+7.46535081e-01*rf_t\n",
+    "print('根据最优权重的线性加权：',accuracy_score(np.argmax(result, axis=1), y_test))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e8ce00b2",
+   "metadata": {},
+   "source": [
+    "可以观察到最优权重比我们主观选权重更优，单对比单模结果反而下降了"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d4a12d6d",
+   "metadata": {},
+   "source": [
+    "### Blending的分数"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "ffe1cf4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wall time: 14min 10s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "blend_ds = pipeline.blend(seed=111)\n",
+    "blender = Classifier(dataset=blend_ds, estimator=LogisticRegression, parameters={\"solver\": 'lbfgs', \"max_iter\": 1000},use_cache=False)\n",
+    "predict_blend = blender.predict()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "506adffb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.9546859617357301\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(accuracy_score(np.argmax(predict_blend, axis=1), y_test))"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "dfec8968",
+   "id": "e84c19ae",
    "metadata": {},
    "source": [
-    "可以观察到最优权重比我们主观选权重更优"
+    "使用Blending的分数有所提升"
    ]
   },
   {
@@ -623,12 +1000,12 @@
    "id": "e8daf1e3",
    "metadata": {},
    "source": [
-    "### stacking的分数"
+    "### Stacking的分数"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 38,
    "id": "4930b407",
    "metadata": {},
    "outputs": [
@@ -636,7 +1013,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.957439777491687\n"
+      "0.9589887988544127\n"
      ]
     }
    ],
@@ -644,12 +1021,20 @@
     "print(accuracy_score(np.argmax(predict_stack, axis=1), y_test))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d5ad3c4b",
+   "metadata": {},
+   "source": [
+    "可以明显看到提升的效果"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "6311fbd7",
    "metadata": {},
    "source": [
-    "## 再说结论，该数据集（fetch_covtype）Stacking的方法更好"
+    "## 再说结论，该数据集（fetch_covtype）Stacking的方法相比Blending和线性加权更好"
    ]
   }
  ],
diff --git a/竞赛优胜技巧/Stacking.ipynb b/竞赛优胜技巧/Stacking.ipynb
index ef7f238..4ae86fe 100644
--- a/竞赛优胜技巧/Stacking.ipynb
+++ b/竞赛优胜技巧/Stacking.ipynb
@@ -13,7 +13,7 @@
    "id": "0b365a02",
    "metadata": {},
    "source": [
-    "## 先说结论，该数据集（fetch_covtype）Stacking的方法比线性加权更好\n",
+    "## 先说结论，该数据集（fetch_covtype）Stacking的方法相比Blending和线性加权更好\n",
     "比赛中我们常用线性加权作为最终的融合方式，我们同样也会好奇怎样的线性加权权重更好，下面也会举例子\n",
     "参考：https://github.com/rushter/heamy/tree/master/examples"
    ]
@@ -67,7 +67,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 1,
    "id": "69632c6a",
    "metadata": {},
    "outputs": [
@@ -86,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 2,
    "id": "ca421279",
    "metadata": {},
    "outputs": [],
@@ -119,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 3,
    "id": "9a0fabe1",
    "metadata": {},
    "outputs": [],
@@ -130,7 +130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 6,
    "id": "5bd75178",
    "metadata": {},
    "outputs": [
@@ -153,14 +153,14 @@
     "print(y)\n",
     "ord = OrdinalEncoder()\n",
     "y = ord.fit_transform(y.reshape(-1, 1))\n",
-    "y = y_enc.reshape(-1, )\n",
+    "y = y.reshape(-1, )\n",
     "print('七分类任务，处理后：',np.unique(y))\n",
     "print(y)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 7,
    "id": "23d9778c",
    "metadata": {},
    "outputs": [
@@ -182,7 +182,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 8,
    "id": "eac48668",
    "metadata": {},
    "outputs": [
@@ -204,7 +204,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 9,
    "id": "fba3f975",
    "metadata": {},
    "outputs": [
@@ -226,7 +226,7 @@
        "        0.000e+00]])"
       ]
      },
-     "execution_count": 50,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -246,7 +246,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 10,
    "id": "e8393e73",
    "metadata": {},
    "outputs": [],
@@ -293,7 +293,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 11,
    "id": "78ab0083",
    "metadata": {},
    "outputs": [],
@@ -313,7 +313,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 13,
    "id": "173ef0f0",
    "metadata": {},
    "outputs": [
@@ -321,185 +321,485 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Best Score (log_loss): 0.18744137777851164\n",
-      "Best Weights: [0.36556831 0.00303401 0.63139768]\n"
+      "Best Score (log_loss): 0.18646435443714865\n",
+      "Best Weights: [2.53464919e-01 1.48562205e-20 7.46535081e-01]\n",
+      "Wall time: 14min 19s\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "array([0.36556831, 0.00303401, 0.63139768])"
+       "array([2.53464919e-01, 1.48562205e-20, 7.46535081e-01])"
       ]
      },
-     "execution_count": 53,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "pipeline.find_weights(scorer=log_loss, )  # 输出最优权重组合"
+    "%%time\n",
+    "pipeline.find_weights(scorer=log_loss)  # 输出最优权重组合"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 22,
    "id": "80726d19",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wall time: 1h 39min 20s\n"
+     ]
+    }
+   ],
    "source": [
+    "%%time\n",
     "# 5折训练构建5折模型特征集，这里比较耗时\n",
-    "stack_ds = pipeline.stack(k=5,stratify=False,seed=42,full_test=False)  # full_test指明预测全部还是预测当前折的验证集"
+    "stack_ds = pipeline.stack(k=5,seed=42)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 26,
    "id": "b25bba3c",
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "           xgb_0     xgb_1         xgb_2         xgb_3         xgb_4  \\\n",
-      "0       0.177179  0.818728  2.185222e-07  9.264143e-09  4.090067e-03   \n",
-      "1       0.005155  0.994845  7.055579e-10  1.326343e-08  6.331572e-09   \n",
-      "2       0.293492  0.706508  3.650662e-10  1.017633e-09  8.823530e-09   \n",
-      "3       0.478112  0.521816  3.207779e-06  2.878019e-08  1.076500e-08   \n",
-      "4       0.992430  0.006652  1.233117e-05  1.887496e-07  1.569583e-06   \n",
-      "...          ...       ...           ...           ...           ...   \n",
-      "435754  0.988518  0.011477  3.190797e-09  5.645121e-08  2.940739e-09   \n",
-      "435755  0.969212  0.030723  2.142020e-08  1.572054e-05  4.321913e-07   \n",
-      "435756  0.415850  0.584142  4.283793e-08  7.367601e-08  6.148067e-07   \n",
-      "435757  0.602601  0.397399  6.606462e-10  1.015894e-09  7.221973e-08   \n",
-      "435758  0.834587  0.165411  3.267833e-09  2.057172e-08  2.078704e-08   \n",
-      "\n",
-      "               xgb_5         xgb_6     lgb_0     lgb_1          lgb_2  ...  \\\n",
-      "0       1.725062e-06  1.048052e-06  0.172406  0.812678   1.416886e-06  ...   \n",
-      "1       1.435787e-09  1.603579e-10  0.008114  0.991886   0.000000e+00  ...   \n",
-      "2       6.384080e-10  2.823794e-08  0.817627  0.182372   0.000000e+00  ...   \n",
-      "3       2.230641e-06  6.630235e-05  0.465733  0.534184   0.000000e+00  ...   \n",
-      "4       5.604260e-07  9.037877e-04  0.932050  0.043451   0.000000e+00  ...   \n",
-      "...              ...           ...       ...       ...            ...  ...   \n",
-      "435754  1.530261e-08  4.466830e-06  0.970593  0.029399   0.000000e+00  ...   \n",
-      "435755  5.574208e-10  4.977021e-05  0.862591  0.136644   0.000000e+00  ...   \n",
-      "435756  2.371389e-06  5.185283e-06  0.466886  0.533039   0.000000e+00  ...   \n",
-      "435757  2.326313e-09  9.193871e-09  0.674250  0.325750  4.092880e-211  ...   \n",
-      "435758  5.976972e-08  2.204258e-06  0.709320  0.290680   0.000000e+00  ...   \n",
-      "\n",
-      "               lgb_4         lgb_5         lgb_6  rf_0  rf_1  rf_2  rf_3  \\\n",
-      "0       1.486358e-02  5.093522e-05  6.805300e-08  0.06  0.92   0.0   0.0   \n",
-      "1       0.000000e+00  0.000000e+00  0.000000e+00  0.12  0.88   0.0   0.0   \n",
-      "2       4.452850e-07  7.825338e-09  1.012052e-07  0.63  0.37   0.0   0.0   \n",
-      "3       0.000000e+00  0.000000e+00  8.245405e-05  0.56  0.44   0.0   0.0   \n",
-      "4       0.000000e+00  0.000000e+00  2.449972e-02  0.95  0.04   0.0   0.0   \n",
-      "...              ...           ...           ...   ...   ...   ...   ...   \n",
-      "435754  0.000000e+00  0.000000e+00  7.871809e-06  0.97  0.03   0.0   0.0   \n",
-      "435755  0.000000e+00  0.000000e+00  7.647430e-04  0.93  0.06   0.0   0.0   \n",
-      "435756  0.000000e+00  0.000000e+00  7.493861e-05  0.45  0.55   0.0   0.0   \n",
-      "435757  0.000000e+00  0.000000e+00  0.000000e+00  0.52  0.48   0.0   0.0   \n",
-      "435758  0.000000e+00  0.000000e+00  0.000000e+00  0.87  0.13   0.0   0.0   \n",
-      "\n",
-      "        rf_4  rf_5  rf_6  \n",
-      "0       0.02   0.0  0.00  \n",
-      "1       0.00   0.0  0.00  \n",
-      "2       0.00   0.0  0.00  \n",
-      "3       0.00   0.0  0.00  \n",
-      "4       0.00   0.0  0.01  \n",
-      "...      ...   ...   ...  \n",
-      "435754  0.00   0.0  0.00  \n",
-      "435755  0.00   0.0  0.01  \n",
-      "435756  0.00   0.0  0.00  \n",
-      "435757  0.00   0.0  0.00  \n",
-      "435758  0.00   0.0  0.00  \n",
-      "\n",
-      "[435759 rows x 21 columns]\n"
-     ]
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>xgb_0</th>\n",
+       "      <th>xgb_1</th>\n",
+       "      <th>xgb_2</th>\n",
+       "      <th>xgb_3</th>\n",
+       "      <th>xgb_4</th>\n",
+       "      <th>xgb_5</th>\n",
+       "      <th>xgb_6</th>\n",
+       "      <th>lgb_0</th>\n",
+       "      <th>lgb_1</th>\n",
+       "      <th>lgb_2</th>\n",
+       "      <th>...</th>\n",
+       "      <th>lgb_4</th>\n",
+       "      <th>lgb_5</th>\n",
+       "      <th>lgb_6</th>\n",
+       "      <th>rf_0</th>\n",
+       "      <th>rf_1</th>\n",
+       "      <th>rf_2</th>\n",
+       "      <th>rf_3</th>\n",
+       "      <th>rf_4</th>\n",
+       "      <th>rf_5</th>\n",
+       "      <th>rf_6</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.177179</td>\n",
+       "      <td>0.818728</td>\n",
+       "      <td>2.185222e-07</td>\n",
+       "      <td>9.264143e-09</td>\n",
+       "      <td>4.090067e-03</td>\n",
+       "      <td>1.725062e-06</td>\n",
+       "      <td>1.048052e-06</td>\n",
+       "      <td>0.179625</td>\n",
+       "      <td>0.804684</td>\n",
+       "      <td>0.000003</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.562435e-02</td>\n",
+       "      <td>6.370849e-05</td>\n",
+       "      <td>1.004259e-08</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.96</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.005155</td>\n",
+       "      <td>0.994845</td>\n",
+       "      <td>7.055579e-10</td>\n",
+       "      <td>1.326343e-08</td>\n",
+       "      <td>6.331572e-09</td>\n",
+       "      <td>1.435787e-09</td>\n",
+       "      <td>1.603579e-10</td>\n",
+       "      <td>0.008114</td>\n",
+       "      <td>0.991886</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>0.87</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.293492</td>\n",
+       "      <td>0.706508</td>\n",
+       "      <td>3.650662e-10</td>\n",
+       "      <td>1.017633e-09</td>\n",
+       "      <td>8.823530e-09</td>\n",
+       "      <td>6.384080e-10</td>\n",
+       "      <td>2.823794e-08</td>\n",
+       "      <td>0.831445</td>\n",
+       "      <td>0.168555</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.999034e-07</td>\n",
+       "      <td>4.015190e-09</td>\n",
+       "      <td>4.997854e-09</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>0.37</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.478112</td>\n",
+       "      <td>0.521816</td>\n",
+       "      <td>3.207779e-06</td>\n",
+       "      <td>2.878019e-08</td>\n",
+       "      <td>1.076500e-08</td>\n",
+       "      <td>2.230641e-06</td>\n",
+       "      <td>6.630235e-05</td>\n",
+       "      <td>0.465733</td>\n",
+       "      <td>0.534184</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>8.245405e-05</td>\n",
+       "      <td>0.55</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.992430</td>\n",
+       "      <td>0.006652</td>\n",
+       "      <td>1.233117e-05</td>\n",
+       "      <td>1.887496e-07</td>\n",
+       "      <td>1.569583e-06</td>\n",
+       "      <td>5.604260e-07</td>\n",
+       "      <td>9.037877e-04</td>\n",
+       "      <td>0.932050</td>\n",
+       "      <td>0.043451</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>2.449972e-02</td>\n",
+       "      <td>0.97</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      xgb_0     xgb_1         xgb_2         xgb_3         xgb_4         xgb_5  \\\n",
+       "0  0.177179  0.818728  2.185222e-07  9.264143e-09  4.090067e-03  1.725062e-06   \n",
+       "1  0.005155  0.994845  7.055579e-10  1.326343e-08  6.331572e-09  1.435787e-09   \n",
+       "2  0.293492  0.706508  3.650662e-10  1.017633e-09  8.823530e-09  6.384080e-10   \n",
+       "3  0.478112  0.521816  3.207779e-06  2.878019e-08  1.076500e-08  2.230641e-06   \n",
+       "4  0.992430  0.006652  1.233117e-05  1.887496e-07  1.569583e-06  5.604260e-07   \n",
+       "\n",
+       "          xgb_6     lgb_0     lgb_1     lgb_2  ...         lgb_4  \\\n",
+       "0  1.048052e-06  0.179625  0.804684  0.000003  ...  1.562435e-02   \n",
+       "1  1.603579e-10  0.008114  0.991886  0.000000  ...  0.000000e+00   \n",
+       "2  2.823794e-08  0.831445  0.168555  0.000000  ...  4.999034e-07   \n",
+       "3  6.630235e-05  0.465733  0.534184  0.000000  ...  0.000000e+00   \n",
+       "4  9.037877e-04  0.932050  0.043451  0.000000  ...  0.000000e+00   \n",
+       "\n",
+       "          lgb_5         lgb_6  rf_0  rf_1  rf_2  rf_3  rf_4  rf_5  rf_6  \n",
+       "0  6.370849e-05  1.004259e-08  0.03  0.96   0.0   0.0  0.01   0.0   0.0  \n",
+       "1  0.000000e+00  0.000000e+00  0.13  0.87   0.0   0.0  0.00   0.0   0.0  \n",
+       "2  4.015190e-09  4.997854e-09  0.63  0.37   0.0   0.0  0.00   0.0   0.0  \n",
+       "3  0.000000e+00  8.245405e-05  0.55  0.45   0.0   0.0  0.00   0.0   0.0  \n",
+       "4  0.000000e+00  2.449972e-02  0.97  0.03   0.0   0.0  0.00   0.0   0.0  \n",
+       "\n",
+       "[5 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
     "# 模型输出的训练集，7个特征对应7个标签的预测概率\n",
-    "print(stack_ds.X_train)"
+    "stack_ds.X_train.head()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 28,
    "id": "835205e9",
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "               xgb_0     xgb_1         xgb_2         xgb_3         xgb_4  \\\n",
-      "0       9.876224e-01  0.000789  2.774616e-06  4.129093e-07  1.311387e-06   \n",
-      "1       5.139124e-02  0.929659  1.852793e-03  1.518293e-07  1.692924e-02   \n",
-      "2       7.695035e-04  0.973729  6.878623e-04  1.573823e-07  2.408167e-02   \n",
-      "3       3.376913e-02  0.966229  2.024872e-07  7.321523e-08  1.071163e-06   \n",
-      "4       1.013981e-03  0.998553  3.794874e-06  8.755425e-08  4.243054e-04   \n",
-      "...              ...       ...           ...           ...           ...   \n",
-      "145248  9.615189e-01  0.038480  6.486028e-08  1.744931e-08  1.069370e-06   \n",
-      "145249  3.055384e-02  0.969440  2.475371e-07  5.530033e-08  4.299908e-06   \n",
-      "145250  8.224608e-06  0.058361  9.212288e-01  9.705171e-08  5.440121e-05   \n",
-      "145251  9.183387e-01  0.081601  5.612090e-08  1.088283e-08  5.225256e-07   \n",
-      "145252  9.203915e-07  0.003578  2.372825e-01  1.582836e-06  3.307252e-07   \n",
-      "\n",
-      "               xgb_5         xgb_6     lgb_0     lgb_1         lgb_2  ...  \\\n",
-      "0       7.851924e-09  1.158422e-02  0.962538  0.004222  9.599869e-23  ...   \n",
-      "1       1.613036e-04  6.763449e-06  0.070947  0.882463  2.232464e-03  ...   \n",
-      "2       7.296442e-04  1.884172e-06  0.004029  0.945838  1.014722e-02  ...   \n",
-      "3       7.227585e-08  1.448203e-09  0.066538  0.933450  1.206630e-06  ...   \n",
-      "4       4.374311e-06  4.566837e-09  0.001334  0.997391  1.580417e-06  ...   \n",
-      "...              ...           ...       ...       ...           ...  ...   \n",
-      "145248  5.049759e-08  4.010809e-07  0.917842  0.082153  2.154302e-17  ...   \n",
-      "145249  1.255851e-08  1.224208e-06  0.058622  0.941370  1.332795e-12  ...   \n",
-      "145250  2.034389e-02  3.132630e-06  0.000268  0.083680  8.789707e-01  ...   \n",
-      "145251  2.566383e-07  5.976933e-05  0.875834  0.123030  2.631276e-12  ...   \n",
-      "145252  7.591362e-01  6.988637e-08  0.000032  0.037757  2.462795e-01  ...   \n",
-      "\n",
-      "                lgb_4         lgb_5          lgb_6   rf_0   rf_1   rf_2  rf_3  \\\n",
-      "0       1.726260e-240  0.000000e+00   3.324009e-02  0.984  0.000  0.000   0.0   \n",
-      "1        4.396802e-02  3.888647e-04   1.077146e-08  0.106  0.816  0.038   0.0   \n",
-      "2        3.329283e-02  6.693269e-03   3.213404e-09  0.008  0.950  0.002   0.0   \n",
-      "3        9.908823e-06  1.371448e-07   1.280235e-09  0.078  0.922  0.000   0.0   \n",
-      "4        1.273086e-03  7.811306e-07   5.594472e-10  0.004  0.988  0.000   0.0   \n",
-      "...               ...           ...            ...    ...    ...    ...   ...   \n",
-      "145248   6.191352e-08  0.000000e+00   4.958509e-06  0.968  0.032  0.000   0.0   \n",
-      "145249   7.656931e-06  3.415083e-47   2.271880e-07  0.018  0.972  0.000   0.0   \n",
-      "145250   2.052535e-04  3.687570e-02   1.393421e-09  0.000  0.040  0.946   0.0   \n",
-      "145251   2.521124e-07  5.749375e-08   1.135236e-03  0.992  0.008  0.000   0.0   \n",
-      "145252   2.927400e-06  7.159244e-01  8.608624e-140  0.000  0.018  0.110   0.0   \n",
-      "\n",
-      "         rf_4   rf_5   rf_6  \n",
-      "0       0.000  0.000  0.016  \n",
-      "1       0.034  0.006  0.000  \n",
-      "2       0.032  0.008  0.000  \n",
-      "3       0.000  0.000  0.000  \n",
-      "4       0.008  0.000  0.000  \n",
-      "...       ...    ...    ...  \n",
-      "145248  0.000  0.000  0.000  \n",
-      "145249  0.010  0.000  0.000  \n",
-      "145250  0.000  0.014  0.000  \n",
-      "145251  0.000  0.000  0.000  \n",
-      "145252  0.000  0.872  0.000  \n",
-      "\n",
-      "[145253 rows x 21 columns]\n"
-     ]
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>xgb_0</th>\n",
+       "      <th>xgb_1</th>\n",
+       "      <th>xgb_2</th>\n",
+       "      <th>xgb_3</th>\n",
+       "      <th>xgb_4</th>\n",
+       "      <th>xgb_5</th>\n",
+       "      <th>xgb_6</th>\n",
+       "      <th>lgb_0</th>\n",
+       "      <th>lgb_1</th>\n",
+       "      <th>lgb_2</th>\n",
+       "      <th>...</th>\n",
+       "      <th>lgb_4</th>\n",
+       "      <th>lgb_5</th>\n",
+       "      <th>lgb_6</th>\n",
+       "      <th>rf_0</th>\n",
+       "      <th>rf_1</th>\n",
+       "      <th>rf_2</th>\n",
+       "      <th>rf_3</th>\n",
+       "      <th>rf_4</th>\n",
+       "      <th>rf_5</th>\n",
+       "      <th>rf_6</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.991493</td>\n",
+       "      <td>0.000210</td>\n",
+       "      <td>4.796058e-06</td>\n",
+       "      <td>6.178684e-08</td>\n",
+       "      <td>6.947614e-07</td>\n",
+       "      <td>2.410490e-09</td>\n",
+       "      <td>8.291459e-03</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>0.99</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.024731</td>\n",
+       "      <td>0.964372</td>\n",
+       "      <td>6.387765e-04</td>\n",
+       "      <td>4.205048e-08</td>\n",
+       "      <td>1.006575e-02</td>\n",
+       "      <td>1.879628e-04</td>\n",
+       "      <td>4.830114e-06</td>\n",
+       "      <td>0.065073</td>\n",
+       "      <td>0.877354</td>\n",
+       "      <td>0.001678</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5.530599e-02</td>\n",
+       "      <td>0.000589</td>\n",
+       "      <td>8.601484e-11</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>0.80</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.000780</td>\n",
+       "      <td>0.979776</td>\n",
+       "      <td>8.593459e-04</td>\n",
+       "      <td>1.267791e-07</td>\n",
+       "      <td>1.710379e-02</td>\n",
+       "      <td>1.477527e-03</td>\n",
+       "      <td>2.521008e-06</td>\n",
+       "      <td>0.005164</td>\n",
+       "      <td>0.933849</td>\n",
+       "      <td>0.016355</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.657553e-02</td>\n",
+       "      <td>0.008057</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.97</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.042695</td>\n",
+       "      <td>0.957304</td>\n",
+       "      <td>2.283268e-08</td>\n",
+       "      <td>4.387427e-08</td>\n",
+       "      <td>4.175481e-07</td>\n",
+       "      <td>4.406019e-08</td>\n",
+       "      <td>6.909629e-10</td>\n",
+       "      <td>0.054392</td>\n",
+       "      <td>0.945608</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.285638e-08</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.96</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.000457</td>\n",
+       "      <td>0.999334</td>\n",
+       "      <td>3.366338e-06</td>\n",
+       "      <td>4.893879e-08</td>\n",
+       "      <td>2.045808e-04</td>\n",
+       "      <td>7.889498e-07</td>\n",
+       "      <td>1.415576e-09</td>\n",
+       "      <td>0.001367</td>\n",
+       "      <td>0.995857</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.776106e-03</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.99</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      xgb_0     xgb_1         xgb_2         xgb_3         xgb_4         xgb_5  \\\n",
+       "0  0.991493  0.000210  4.796058e-06  6.178684e-08  6.947614e-07  2.410490e-09   \n",
+       "1  0.024731  0.964372  6.387765e-04  4.205048e-08  1.006575e-02  1.879628e-04   \n",
+       "2  0.000780  0.979776  8.593459e-04  1.267791e-07  1.710379e-02  1.477527e-03   \n",
+       "3  0.042695  0.957304  2.283268e-08  4.387427e-08  4.175481e-07  4.406019e-08   \n",
+       "4  0.000457  0.999334  3.366338e-06  4.893879e-08  2.045808e-04  7.889498e-07   \n",
+       "\n",
+       "          xgb_6     lgb_0     lgb_1     lgb_2  ...         lgb_4     lgb_5  \\\n",
+       "0  8.291459e-03  0.000000  0.000000  0.000000  ...  0.000000e+00  0.000000   \n",
+       "1  4.830114e-06  0.065073  0.877354  0.001678  ...  5.530599e-02  0.000589   \n",
+       "2  2.521008e-06  0.005164  0.933849  0.016355  ...  3.657553e-02  0.008057   \n",
+       "3  6.909629e-10  0.054392  0.945608  0.000000  ...  4.285638e-08  0.000000   \n",
+       "4  1.415576e-09  0.001367  0.995857  0.000000  ...  2.776106e-03  0.000000   \n",
+       "\n",
+       "          lgb_6  rf_0  rf_1  rf_2  rf_3  rf_4  rf_5  rf_6  \n",
+       "0  1.000000e+00  0.99  0.00  0.00   0.0  0.00  0.00  0.01  \n",
+       "1  8.601484e-11  0.09  0.80  0.05   0.0  0.06  0.00  0.00  \n",
+       "2  0.000000e+00  0.01  0.97  0.00   0.0  0.01  0.01  0.00  \n",
+       "3  0.000000e+00  0.04  0.96  0.00   0.0  0.00  0.00  0.00  \n",
+       "4  0.000000e+00  0.00  0.99  0.00   0.0  0.01  0.00  0.00  \n",
+       "\n",
+       "[5 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
     "# 模型输出的测试集，7个特征对应7个标签的预测概率\n",
-    "print(stack_ds.X_test) "
+    "stack_ds.X_test.head()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 30,
    "id": "b9db35dc",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wall time: 1min 53s\n"
+     ]
+    }
+   ],
    "source": [
+    "%%time\n",
     "# 用lr做最后一层\n",
     "stacker = Classifier(dataset=stack_ds, estimator=LogisticRegression, parameters={\"solver\": 'lbfgs', \"max_iter\": 1000},use_cache=False)\n",
     "predict_stack = stacker.predict()"
@@ -507,7 +807,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 32,
    "id": "a4a48219",
    "metadata": {},
    "outputs": [
@@ -515,19 +815,19 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[9.95173402e-01 2.67623709e-03 4.23846755e-08 ... 3.15435935e-05\n",
-      "  5.66194220e-06 2.11044140e-03]\n",
-      " [2.23612439e-02 9.70927685e-01 1.23929922e-03 ... 4.49727904e-03\n",
-      "  8.73983383e-04 9.97020226e-05]\n",
-      " [6.22588197e-03 9.89402233e-01 9.81655972e-04 ... 2.83331258e-03\n",
-      "  5.22139184e-04 3.45071569e-05]\n",
+      "[[9.99137967e-01 4.76574513e-04 3.32764186e-07 ... 3.03237700e-06\n",
+      "  1.62161211e-06 3.79326620e-04]\n",
+      " [2.00732175e-02 9.71682830e-01 1.51484266e-03 ... 5.69138554e-03\n",
+      "  9.40725428e-04 9.60822625e-05]\n",
+      " [5.54556002e-03 9.91048437e-01 8.04840682e-04 ... 2.11437934e-03\n",
+      "  4.56463787e-04 3.00919502e-05]\n",
       " ...\n",
-      " [5.36335125e-06 2.06267200e-03 9.90604140e-01 ... 8.55252386e-04\n",
-      "  4.18405061e-03 1.64678945e-05]\n",
-      " [9.96602824e-01 2.15991442e-03 7.27481581e-08 ... 3.63552051e-05\n",
-      "  6.80942632e-06 1.19199377e-03]\n",
-      " [5.89156494e-05 1.15333400e-03 1.09178439e-02 ... 3.09244417e-04\n",
-      "  9.85167196e-01 2.21261408e-05]]\n"
+      " [4.60179790e-06 1.78298095e-03 9.91553958e-01 ... 7.26752933e-04\n",
+      "  3.79135124e-03 1.53584401e-05]\n",
+      " [9.96307096e-01 2.43558944e-03 1.01596361e-07 ... 3.94985596e-05\n",
+      "  7.41569805e-06 1.20819024e-03]\n",
+      " [5.34671504e-05 7.62534718e-04 5.58323657e-03 ... 2.11410908e-04\n",
+      "  9.91805379e-01 1.69502656e-05]]\n"
      ]
     }
    ],
@@ -553,7 +853,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 33,
    "id": "a28806a0",
    "metadata": {},
    "outputs": [
@@ -561,9 +861,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.9284696357390209\n",
-      "0.8890005714167694\n",
-      "0.9511404239499356\n"
+      "0.9254473229468583\n",
+      "0.8412562907478676\n",
+      "0.9535087055000585\n"
      ]
     }
    ],
@@ -573,6 +873,28 @@
     "print(accuracy_score(np.argmax(stack_ds.X_test.iloc[:, 14:].values, axis=1),y_test))  # RF"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "1db92fec",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.9537840870756542\n",
+      "Wall time: 50.8 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# 测试单模运行结果是否一致\n",
+    "rf_predict = rf_model(X_train, y_train, X_test, None)\n",
+    "print(accuracy_score(np.argmax(rf_predict, axis=1),y_test))  # RF"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "2e9423ce",
@@ -583,7 +905,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 37,
    "id": "d2b50ba4",
    "metadata": {},
    "outputs": [
@@ -591,8 +913,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "主观根据结果blending： 0.9425209806337908\n",
-      "根据最优权重的blending： 0.9488616414118813\n"
+      "主观根据结果blending： 0.9504106627746071\n",
+      "根据最优权重的线性加权： 0.9530749795184953\n"
      ]
     }
    ],
@@ -603,19 +925,74 @@
     "rf_t = stack_ds.X_test.iloc[:, 14:].values\n",
     "\n",
     "# 根据分数好坏随机定\n",
-    "result = 0.3*xgb_t+0.2*lgb_t+0.5*rf_t\n",
+    "result = 0.2*xgb_t+0.1*lgb_t+0.7*rf_t\n",
     "print('主观根据结果blending：', accuracy_score(np.argmax(result, axis=1), y_test))\n",
-    "# 根据上面提供的最优权重 Best Weights: [0.36556831 0.00303401 0.63139768]\n",
-    "result =  0.36556831*xgb_t+0.00303401*lgb_t+0.63139768*rf_t\n",
-    "print('根据最优权重的blending：',accuracy_score(np.argmax(result, axis=1), y_test))"
+    "# 根据上面提供的最优权重 Best Weights: [2.53464919e-01 1.48562205e-20 7.46535081e-01]\n",
+    "result =  2.53464919e-01*xgb_t+1.48562205e-20*lgb_t+7.46535081e-01*rf_t\n",
+    "print('根据最优权重的线性加权：',accuracy_score(np.argmax(result, axis=1), y_test))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e8ce00b2",
+   "metadata": {},
+   "source": [
+    "可以观察到最优权重比我们主观选权重更优，单对比单模结果反而下降了"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d4a12d6d",
+   "metadata": {},
+   "source": [
+    "### Blending的分数"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "ffe1cf4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wall time: 14min 10s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "blend_ds = pipeline.blend(seed=111)\n",
+    "blender = Classifier(dataset=blend_ds, estimator=LogisticRegression, parameters={\"solver\": 'lbfgs', \"max_iter\": 1000},use_cache=False)\n",
+    "predict_blend = blender.predict()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "506adffb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.9546859617357301\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(accuracy_score(np.argmax(predict_blend, axis=1), y_test))"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "dfec8968",
+   "id": "e84c19ae",
    "metadata": {},
    "source": [
-    "可以观察到最优权重比我们主观选权重更优"
+    "使用Blending的分数有所提升"
    ]
   },
   {
@@ -623,12 +1000,12 @@
    "id": "e8daf1e3",
    "metadata": {},
    "source": [
-    "### stacking的分数"
+    "### Stacking的分数"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 38,
    "id": "4930b407",
    "metadata": {},
    "outputs": [
@@ -636,7 +1013,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.957439777491687\n"
+      "0.9589887988544127\n"
      ]
     }
    ],
@@ -644,12 +1021,20 @@
     "print(accuracy_score(np.argmax(predict_stack, axis=1), y_test))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d5ad3c4b",
+   "metadata": {},
+   "source": [
+    "可以明显看到提升的效果"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "6311fbd7",
    "metadata": {},
    "source": [
-    "## 再说结论，该数据集（fetch_covtype）Stacking的方法更好"
+    "## 再说结论，该数据集（fetch_covtype）Stacking的方法相比Blending和线性加权更好"
    ]
   }
  ],