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ML-For-Beginners/translations/zh-CN/4-Classification/3-Classifiers-2/notebook.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 构建分类模型\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Unnamed: 0 cuisine almond angelica anise anise_seed apple \\\n",
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"1 0 0 0 0 0 0 0 \n",
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"\n",
"[5 rows x 382 columns]"
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},
"metadata": {},
"execution_count": 9
}
],
"source": [
"import pandas as pd\n",
"cuisines_df = pd.read_csv(\"../data/cleaned_cuisines.csv\")\n",
"cuisines_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"0 indian\n",
"1 indian\n",
"2 indian\n",
"3 indian\n",
"4 indian\n",
"Name: cuisine, dtype: object"
]
},
"metadata": {},
"execution_count": 10
}
],
"source": [
"cuisines_label_df = cuisines_df['cuisine']\n",
"cuisines_label_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" almond angelica anise anise_seed apple apple_brandy apricot \\\n",
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"\n",
" armagnac artemisia artichoke ... whiskey white_bread white_wine \\\n",
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"\n",
"[5 rows x 380 columns]"
],
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},
"metadata": {},
"execution_count": 11
}
],
"source": [
"cuisines_features_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n",
"cuisines_features_df.head()"
]
},
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"cell_type": "markdown",
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"---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**免责声明**\n本文件由 AI 翻译服务 [Co-op Translator](https://github.com/Azure/co-op-translator) 翻译而成。尽管我们力求准确,但请注意,自动翻译可能包含错误或不准确之处。原始文件的原文应视为权威来源。对于重要信息,建议使用专业人工翻译。我们不对因使用本翻译而产生的任何误解或误读承担责任。\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
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