Logistic Regression: Test Your Knowledge Return to pathway Why is a linear regression model's output a poor predictor of probability? It only has one weight per feature. It only has one output value. The bias parameter skews the output value. Its predictions are not restricted to values between 0 and 1. True or false: A sigmoid function never outputs the value 0 or the value 1. True False True or false: Applying regularization is less important when training logistic regression models than it is for training linear regression models. True False Which of the following options matches both Linear Regression and Logistic Regression with appropriate loss functions for calculating loss? Linear Regression: Mean squared error Logistic Regression: Mean squared error Linear Regression: Mean squared error Logistic Regression: Mean absolute error Linear Regression: Mean squared error Logistic Regression: Log Loss Linear Regression: Log Loss Logistic Regression: Mean squared error Which of the following is an effective regularization technique for logistic regression models? Dropout regularization Late stopping Early stopping Gradient descent Submit answers error_outline An error occurred when grading the quiz. Please try again.
