How do you evaluate a classification model?
Using a Confusion Matrix, Accuracy, Precision, Recall, and AUC-ROC score.
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More FAQs in What is Logistic Regression? Binary Classification Explained
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.
When the model incorrectly predicts class 1 (positive) when the actual value is class 0 (negative).
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