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Update decision_tree.py
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@ -164,7 +164,7 @@ def main():
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to predict the label of 10 different test values. Here we should prefer
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to predict the label of 10 different test values. Here we should prefer
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calculating Root Mean Squared Error over Mean Sqaured error because RMSE
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calculating Root Mean Squared Error over Mean Sqaured error because RMSE
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should be used when you need to communicate your results in an understandable
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should be used when you need to communicate your results in an understandable
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way to end users or when penalising outliers is less of a priority.Interpretation will be easy in this case.
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way to end users or when penalising outliers is less of a priority.
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"""
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"""
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x = np.arange(-1.0, 1.0, 0.005)
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x = np.arange(-1.0, 1.0, 0.005)
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y = np.sin(x)
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y = np.sin(x)
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