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19 lines
504 B
19 lines
504 B
from sklearn.linear_model import LinearRegression
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def perform_regression(data, data_name, target_name):
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X = data[data_name]
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y = data[target_name]
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if not isinstance(y.iloc[0], (int, float)):
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raise ValueError("The target variable should be numeric (continuous) for regression.")
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model = LinearRegression()
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model.fit(X, y)
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return model
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def make_prediction(model, feature_names, input_values):
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prediction = model.predict([input_values])
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return prediction[0]
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