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base state for notebooks - classification 3
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Build Classification Model" | ||
| ] | ||
| }, | ||
| { | ||
| "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", | ||
| "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]" | ||
| ], | ||
| "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>" | ||
| }, | ||
| "metadata": {}, | ||
| "execution_count": 9 | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import pandas as pd\n", | ||
| "recipes_df = pd.read_csv(\"../data/cleaned_cuisine.csv\")\n", | ||
| "recipes_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": [ | ||
| "recipes_label_df = recipes_df['cuisine']\n", | ||
| "recipes_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", | ||
| "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]" | ||
| ], | ||
| "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>" | ||
| }, | ||
| "metadata": {}, | ||
| "execution_count": 11 | ||
| } | ||
| ], | ||
| "source": [ | ||
| "recipes_feature_df = recipes_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n", | ||
| "recipes_feature_df.head()" | ||
| ] | ||
| } | ||
| ], | ||
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| "name": "python3", | ||
| "display_name": "Python 3.7.0 64-bit ('3.7')" | ||
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| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
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| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
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| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
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