Choose the dependent variable (the response variable to be "explained") and the independent variable (the predictor or explanatory variable). Dependent Variable O Power O Speed Independent Variable Y= O Power O Speed Obtain the regression equation. (Round your answers to 3 decimal places.) X+ Calculate R². (Round your answer to 3 decimal places.)

If we decrease the significance level (alpha) all else being equal, the power of the test will:   A. Won't change   B. Increase   C. Decrease   D. It depends – need more information

You have trained a logistic regression classifier and planned to make predictions according to: Predict y=1 if ho(x) 2 threshold Predict y=0 if ho (x) < threshold For different threshold values, you get different values of precision (P) and recall (R). Which of the following is a reasonable way to pick the threshold value? O a Measure precision (P) and recall (R) on the test set and choose the value of P+R threshold which maximizes 2 Ob Measure precision (P) and recall (R) on the cross validation set and choose the P+R value of threshold which maximizes 2 Measure precision (P) and recall (R) on the cross validation set and choose the PR value of threshold which maximizes 2 P+R Measure precision (P) and recall (R) on the test set and choose the value of PR threshold which maximizes 2 P+R

Which statements are true about LASSO linear regression?   Group of answer choices has embedded variable selection by shrinking the coefficient of some variables to exactly zero. has one hyper-parameter lambda (The regularization coefficient) which needs to be tuned if there are multiple correlated predictors lasso will select all of them adds the L2 norm of the coefficients as penalty to the loss function to penalize larger coefficients