{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Izgradnja modela za klasifikaciju\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", "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": "
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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", "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": "
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" }, "metadata": {}, "execution_count": 11 } ], "source": [ "cuisines_feature_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n", "cuisines_feature_df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n---\n\n**Odricanje od odgovornosti**: \nOvaj dokument je preveden korištenjem AI usluge za prevođenje [Co-op Translator](https://github.com/Azure/co-op-translator). Iako nastojimo osigurati točnost, imajte na umu da automatski prijevodi mogu sadržavati pogreške ili netočnosti. Izvorni dokument na izvornom jeziku treba smatrati mjerodavnim izvorom. Za ključne informacije preporučuje se profesionalni prijevod od strane stručnjaka. Ne preuzimamo odgovornost za bilo kakve nesporazume ili pogrešne interpretacije proizašle iz korištenja ovog prijevoda.\n" ] } ], "metadata": { "interpreter": { "hash": "70b38d7a306a849643e446cd70466270a13445e5987dfa1344ef2b127438fa4d" }, "kernelspec": { "name": "python3", "display_name": "Python 3.7.0 64-bit ('3.7')" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.0" }, "metadata": { "interpreter": { "hash": "70b38d7a306a849643e446cd70466270a13445e5987dfa1344ef2b127438fa4d" } }, "coopTranslator": { "original_hash": "15a83277036572e0773229b5f21c1e12", "translation_date": "2025-09-04T08:32:08+00:00", "source_file": "4-Classification/3-Classifiers-2/notebook.ipynb", "language_code": "hr" } }, "nbformat": 4, "nbformat_minor": 4 }