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July 27, 2019 13:09
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Data Preparation
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| y = data.dropna().y | |
| X = data.dropna().drop(['y'], axis=1) | |
| # Reserve 30% of data for testing | |
| X_train, X_test, y_train, y_test = timeseries_train_test_split(X, y, test_size=0.3) | |
| X_train_scaled = scaler.fit_transform(X_train) | |
| X_test_scaled = scaler.transform(X_test) | |
| # Linear Regression | |
| lr = LinearRegression() | |
| lr.fit(X_train_scaled, y_train) | |
| plotModelResults(lr, X_train_scaled, X_test_scaled, plot_intervals=False) |
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