Question: = Pr (Y = 1) Imagine you have a classification data where the target y takes values 0 or 1. If p then the value

= Pr (Y = 1) Imagine you have a classification

= Pr (Y = 1) Imagine you have a classification data where the target y takes values 0 or 1. If p then the value of Odds (Y = 0) is ile all Op(1 p) Which of the following is a plausible logistics response function with one predictor X1? 1 1+e-(Bo+B1-X1) 1 1+e(Bo+B1-81) None of the remaining choices e e-(Bo+B1-X1) ite-(Bo+B1-X1) Consider the following confusion matrix with two classes C1 and C2, and let "n" be the total number of observations in the validation dataset. For example, n11 represents the number of observations for whom actual output is C and Prediction is C1. A similar interpretation follows for N12, 121, 122- (Assume C1 is an important class) Actual/Reference C1 C2 C1 nu n12 Prediction n21 n22 Overall Accuracy can also be computed using the formula O (111+122) Sensitivity. Specificity 111-Specificity - 122-Sensitivity o (n11+122) Sensitivity Specificity n11.Sensitivity - 122.Specificity O (111+122) Sensitivity Specificity n11. Specificity + n22-Sensitivity O (111+1222). Sensitivity.Specificity n11.Sensitivity +1122Specificity

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