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

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 建立分類模型\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
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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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"1 1 0 0 0 0 0 0 \n",
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"\n",
" armagnac artemisia artichoke ... whiskey white_bread white_wine \\\n",
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"\n",
" whole_grain_wheat_flour wine wood yam yeast yogurt zucchini \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()"
]
},
{
"cell_type": "markdown",
"metadata": {},
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"---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**免責聲明** \n本文件由 AI 翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 翻譯而成。雖然我們力求準確,但請注意自動翻譯可能包含錯誤或不準確之處。原始文件的母語版本應被視為權威來源。對於重要資訊,建議使用專業人工翻譯。我們對因使用本翻譯而引起的任何誤解或曲解概不負責。\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
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