The answer
Yes, by adding interaction terms or polynomial features to the input data.
Yes, by adding interaction terms or polynomial features to the input data.
Linear regression can output values greater than 1 or less than 0, making it unsuitable for probabilities. It is also sensitive to outliers.
It is an S-shaped curve that asymptoticly approaches 0 and 1.
Using a Confusion Matrix, Accuracy, Precision, Recall, and AUC-ROC score.
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