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1. DecisionTreeRegressor DecisionTreeRegressor

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   Y = home_data.SalePrice

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   feature_names = ["LotArea","YearBuilt","1stFlrSF","2ndFlrSF","FullBath","BedroomAbvGr","TotRmsAbvGrd"]

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   X = home_data[feature_names]

2. Article2 Article2

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   from sklearn.model_selection import train_test_split

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   train_X, val_X, train_y, val_y = train_test_split(X,y,random_state=1)

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   iowa_model = DecisionTreeRegressor(random_state=1)

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   iowa_model.fit(train_X,train_y)

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   val_predictions = iowa_model.predict(val_X)

3. reliveIndia reliveIndia Public

   NGO Website

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4. portfolio portfolio Public

   A static web page about me

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