From a5f5ad4a12fce5e8408f8a0e197421421eba0b44 Mon Sep 17 00:00:00 2001
From: Paskal Sunari <60564521+PaskalSunari@users.noreply.github.com>
Date: Thu, 12 Jun 2025 10:23:24 +0000
Subject: [PATCH 1/2] classifir 1

---
 .../1-Introduction/notebook.ipynb             |   2 +-
 .../2-Classifiers-1/notebook.ipynb            | 552 +++++++++++++++++-
 2 files changed, 541 insertions(+), 13 deletions(-)

diff --git a/4-Classification/1-Introduction/notebook.ipynb b/4-Classification/1-Introduction/notebook.ipynb
index fd862c35..f85e06e6 100644
--- a/4-Classification/1-Introduction/notebook.ipynb
+++ b/4-Classification/1-Introduction/notebook.ipynb
@@ -747,7 +747,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.3"
+   "version": "3.11.4"
   },
   "orig_nbformat": 2
  },
diff --git a/4-Classification/2-Classifiers-1/notebook.ipynb b/4-Classification/2-Classifiers-1/notebook.ipynb
index 30778dee..2b51e68c 100644
--- a/4-Classification/2-Classifiers-1/notebook.ipynb
+++ b/4-Classification/2-Classifiers-1/notebook.ipynb
@@ -1,5 +1,542 @@
 {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Build Classification Models"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## predict a national cuisine"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>Unnamed: 0</th>\n",
+       "      <th>cuisine</th>\n",
+       "      <th>almond</th>\n",
+       "      <th>angelica</th>\n",
+       "      <th>anise</th>\n",
+       "      <th>anise_seed</th>\n",
+       "      <th>apple</th>\n",
+       "      <th>apple_brandy</th>\n",
+       "      <th>apricot</th>\n",
+       "      <th>armagnac</th>\n",
+       "      <th>...</th>\n",
+       "      <th>whiskey</th>\n",
+       "      <th>white_bread</th>\n",
+       "      <th>white_wine</th>\n",
+       "      <th>whole_grain_wheat_flour</th>\n",
+       "      <th>wine</th>\n",
+       "      <th>wood</th>\n",
+       "      <th>yam</th>\n",
+       "      <th>yeast</th>\n",
+       "      <th>yogurt</th>\n",
+       "      <th>zucchini</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>indian</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>indian</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>indian</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>indian</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>indian</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 382 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Unnamed: 0 cuisine  almond  angelica  anise  anise_seed  apple  \\\n",
+       "0           0  indian       0         0      0           0      0   \n",
+       "1           1  indian       1         0      0           0      0   \n",
+       "2           2  indian       0         0      0           0      0   \n",
+       "3           3  indian       0         0      0           0      0   \n",
+       "4           4  indian       0         0      0           0      0   \n",
+       "\n",
+       "   apple_brandy  apricot  armagnac  ...  whiskey  white_bread  white_wine  \\\n",
+       "0             0        0         0  ...        0            0           0   \n",
+       "1             0        0         0  ...        0            0           0   \n",
+       "2             0        0         0  ...        0            0           0   \n",
+       "3             0        0         0  ...        0            0           0   \n",
+       "4             0        0         0  ...        0            0           0   \n",
+       "\n",
+       "   whole_grain_wheat_flour  wine  wood  yam  yeast  yogurt  zucchini  \n",
+       "0                        0     0     0    0      0       0         0  \n",
+       "1                        0     0     0    0      0       0         0  \n",
+       "2                        0     0     0    0      0       0         0  \n",
+       "3                        0     0     0    0      0       0         0  \n",
+       "4                        0     0     0    0      0       1         0  \n",
+       "\n",
+       "[5 rows x 382 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "cuisines_df = pd.read_csv(\"../data/cleaned_cuisines.csv\")\n",
+    "cuisines_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.model_selection import train_test_split, cross_val_score\n",
+    "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report, precision_recall_curve, precision_score\n",
+    "from sklearn.svm import SVC\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    indian\n",
+       "1    indian\n",
+       "2    indian\n",
+       "3    indian\n",
+       "4    indian\n",
+       "Name: cuisine, dtype: object"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cuisines_label_df = cuisines_df['cuisine']\n",
+    "cuisines_label_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "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>almond</th>\n",
+       "      <th>angelica</th>\n",
+       "      <th>anise</th>\n",
+       "      <th>anise_seed</th>\n",
+       "      <th>apple</th>\n",
+       "      <th>apple_brandy</th>\n",
+       "      <th>apricot</th>\n",
+       "      <th>armagnac</th>\n",
+       "      <th>artemisia</th>\n",
+       "      <th>artichoke</th>\n",
+       "      <th>...</th>\n",
+       "      <th>whiskey</th>\n",
+       "      <th>white_bread</th>\n",
+       "      <th>white_wine</th>\n",
+       "      <th>whole_grain_wheat_flour</th>\n",
+       "      <th>wine</th>\n",
+       "      <th>wood</th>\n",
+       "      <th>yam</th>\n",
+       "      <th>yeast</th>\n",
+       "      <th>yogurt</th>\n",
+       "      <th>zucchini</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 380 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   almond  angelica  anise  anise_seed  apple  apple_brandy  apricot  \\\n",
+       "0       0         0      0           0      0             0        0   \n",
+       "1       1         0      0           0      0             0        0   \n",
+       "2       0         0      0           0      0             0        0   \n",
+       "3       0         0      0           0      0             0        0   \n",
+       "4       0         0      0           0      0             0        0   \n",
+       "\n",
+       "   armagnac  artemisia  artichoke  ...  whiskey  white_bread  white_wine  \\\n",
+       "0         0          0          0  ...        0            0           0   \n",
+       "1         0          0          0  ...        0            0           0   \n",
+       "2         0          0          0  ...        0            0           0   \n",
+       "3         0          0          0  ...        0            0           0   \n",
+       "4         0          0          0  ...        0            0           0   \n",
+       "\n",
+       "   whole_grain_wheat_flour  wine  wood  yam  yeast  yogurt  zucchini  \n",
+       "0                        0     0     0    0      0       0         0  \n",
+       "1                        0     0     0    0      0       0         0  \n",
+       "2                        0     0     0    0      0       0         0  \n",
+       "3                        0     0     0    0      0       0         0  \n",
+       "4                        0     0     0    0      0       1         0  \n",
+       "\n",
+       "[5 rows x 380 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cusisines_features_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n",
+    "cusisines_features_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train, X_test, y_train, y_test = train_test_split(cusisines_features_df, cuisines_label_df, test_size=0.3, random_state=42)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Logistic Regression Accuracy: 0.79\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/workspaces/ML-For-Beginners/.venv/lib/python3.11/site-packages/sklearn/linear_model/_logistic.py:1256: FutureWarning: 'multi_class' was deprecated in version 1.5 and will be removed in 1.7. Use OneVsRestClassifier(LogisticRegression(..)) instead. Leave it to its default value to avoid this warning.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "lr = LogisticRegression(multi_class = 'ovr', solver='liblinear')\n",
+    "model = lr.fit(X_train, np.ravel(y_train))\n",
+    "accuracy = model.score(X_test, y_test)\n",
+    "print(f\"Logistic Regression Accuracy: {accuracy:.2f}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ingredients: Index(['fish', 'lime_juice', 'shallot'], dtype='object')\n",
+      "cuisine: thai\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f'ingredients: {X_test.iloc[50][X_test.iloc[50]!=0].keys()}')\n",
+    "print(f'cuisine: {y_test.iloc[50]}')"
+   ]
+  }
+ ],
  "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
@@ -10,19 +547,10 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": 3
+   "version": "3.11.4"
   },
   "orig_nbformat": 2
  },
  "nbformat": 4,
- "nbformat_minor": 2,
- "cells": [
-  {
-   "source": [
-    "# Build Classification Models"
-   ],
-   "cell_type": "markdown",
-   "metadata": {}
-  }
- ]
-}
\ No newline at end of file
+ "nbformat_minor": 2
+}

From 46ec25562ba90e1ea7748e32a3bebdb50040950b Mon Sep 17 00:00:00 2001
From: Paskal Sunari <60564521+PaskalSunari@users.noreply.github.com>
Date: Thu, 12 Jun 2025 17:25:59 +0000
Subject: [PATCH 2/2] claffification 1 finished

---
 .../2-Classifiers-1/notebook.ipynb            | 135 ++++++++++++++++--
 1 file changed, 125 insertions(+), 10 deletions(-)

diff --git a/4-Classification/2-Classifiers-1/notebook.ipynb b/4-Classification/2-Classifiers-1/notebook.ipynb
index 2b51e68c..342f51c8 100644
--- a/4-Classification/2-Classifiers-1/notebook.ipynb
+++ b/4-Classification/2-Classifiers-1/notebook.ipynb
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -214,7 +214,7 @@
        "[5 rows x 382 columns]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -227,7 +227,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -240,7 +240,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -254,7 +254,7 @@
        "Name: cuisine, dtype: object"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -266,7 +266,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -464,7 +464,7 @@
        "[5 rows x 380 columns]"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -476,7 +476,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -485,7 +485,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -513,7 +513,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -529,6 +529,121 @@
     "print(f'ingredients: {X_test.iloc[50][X_test.iloc[50]!=0].keys()}')\n",
     "print(f'cuisine: {y_test.iloc[50]}')"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/workspaces/ML-For-Beginners/.venv/lib/python3.11/site-packages/sklearn/utils/validation.py:2739: UserWarning: X does not have valid feature names, but LogisticRegression was fitted with feature names\n",
+      "  warnings.warn(\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>0</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>thai</th>\n",
+       "      <td>0.839568</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>japanese</th>\n",
+       "      <td>0.134624</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>chinese</th>\n",
+       "      <td>0.014531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>korean</th>\n",
+       "      <td>0.008383</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>indian</th>\n",
+       "      <td>0.002894</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 0\n",
+       "thai      0.839568\n",
+       "japanese  0.134624\n",
+       "chinese   0.014531\n",
+       "korean    0.008383\n",
+       "indian    0.002894"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test= X_test.iloc[50].values.reshape(-1, 1).T\n",
+    "proba = model.predict_proba(test)\n",
+    "classes = model.classes_\n",
+    "resultdf = pd.DataFrame(data=proba, columns=classes)\n",
+    "\n",
+    "topPrediction = resultdf.T.sort_values(by=[0], ascending = [False])\n",
+    "topPrediction.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "     chinese       0.69      0.69      0.69       236\n",
+      "      indian       0.91      0.91      0.91       245\n",
+      "    japanese       0.73      0.72      0.73       231\n",
+      "      korean       0.81      0.76      0.78       242\n",
+      "        thai       0.78      0.84      0.81       245\n",
+      "\n",
+      "    accuracy                           0.79      1199\n",
+      "   macro avg       0.79      0.78      0.78      1199\n",
+      "weighted avg       0.79      0.79      0.79      1199\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "y_pred = model.predict(X_test)\n",
+    "print(classification_report(y_test, y_pred))"
+   ]
   }
  ],
  "metadata": {