75 lines
2.3 KiB
Python
75 lines
2.3 KiB
Python
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from flask import Flask, render_template, request
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import pandas as pd
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from sklearn.model_selection import train_test_split
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from sklearn.linear_model import Lasso
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from sklearn.preprocessing import OneHotEncoder
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from sklearn.compose import ColumnTransformer
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from sklearn.pipeline import Pipeline
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from sklearn.metrics import mean_squared_error
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import joblib
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app = Flask(__name__)
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# Загрузка данных
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data = pd.read_csv('top_240_restaurants_recommended_in_los_angeles_2.csv')
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# Выбор нужных столбцов
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selected_columns = ['Rank', 'StarRating', 'NumberOfReviews', 'Style']
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data = data[selected_columns]
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# Кодирование столбца Style
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encoder = OneHotEncoder(sparse=False)
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encoded_styles = encoder.fit_transform(data[['Style']])
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encoded_styles_df = pd.DataFrame(encoded_styles, columns=encoder.get_feature_names_out(['Style']))
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data = pd.concat([data, encoded_styles_df], axis=1).drop('Style', axis=1)
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# Разделение данных
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X = data.drop('Rank', axis=1)
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y = data['Rank']
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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
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# Обучение модели
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lasso_model = Pipeline([
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('lasso', Lasso(alpha=0.1))
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])
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lasso_model.fit(X_train, y_train)
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# Сохранение модели
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joblib.dump(lasso_model, 'lasso_model.joblib')
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# Загрузка модели
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lasso_model = joblib.load('lasso_model.joblib')
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@app.route('/')
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def index():
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return render_template('index.html')
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@app.route('/predict', methods=['POST'])
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def predict():
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if request.method == 'POST':
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# Получение данных из формы
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input_data = {
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'StarRating': float(request.form['StarRating']),
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'NumberOfReviews': int(request.form['NumberOfReviews']),
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'Style': request.form['Style']
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}
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# Кодирование стиля
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input_style_encoded = encoder.transform([[input_data['Style']]])
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input_data.pop('Style')
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input_data.update(dict(zip(encoded_styles_df.columns, input_style_encoded[0])))
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# Преобразование данных в DataFrame
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input_df = pd.DataFrame([input_data])
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# Предсказание
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prediction = lasso_model.predict(input_df)[0]
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return render_template('index.html', prediction=prediction)
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if __name__ == '__main__':
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app.run(debug=True)
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