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q1) a. Measure the precision (P) and recall (R) on the cross validation set and choose the value of threshold which maximizes 2 * (PR)/(P + R)  b. Measure the precision (P) and recall (R) on the test set and choose the value of threshold which maximizes 2 * (PR)/(P + R)  c. Measure the precision (P) and recall (R) on the cross validation set and choose the value of threshold which maximizes (P + R)/2 d. Measure the precision (P) and recall (R) on the test set and choose the value of threshold which maximizes (P + R)/2

q1) a. Measure the precision (P) and recall (R) on the cross validation set and choose the value of threshold which maximizes 2 * (PR)/(P + R)  b. Measure the precision (P) and recall (R) on the test set and choose the value of threshold which maximizes 2 * (PR)/(P + R)  c. Measure the precision (P) and recall (R) on the cross validation set and choose the value of threshold which maximizes (P + R)/2 d. Measure the precision (P) and recall (R) on the test set and choose the value of threshold which maximizes (P + R)/2

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q1)
a. Measure the precision (P) and recall (R) on the cross validation set and choose the value of threshold which maximizes 2 * (PR)/(P + R) 
b. Measure the precision (P) and recall (R) on the test set and choose the value of threshold which maximizes 2 * (PR)/(P + R) 
c. Measure the precision (P) and recall (R) on the cross validation set and choose the value of threshold which maximizes (P + R)/2
d. Measure the precision (P) and recall (R) on the test set and choose the value of threshold which maximizes (P + R)/2

q2) Consider the model selection procedure where we choose the degree of polynomials, d,
    by using the cross validation set. For the final model (with parameters theta), we might generally expect Jcv (theta) to be lower than Jtest (theta) because
a)The parameter, d, has been fit to the cross validation set.
b)The parameter, d, has been fit to the test set.
c)The cross validation set is usually smaller than the test set. 
d)The cross validation set is usually larger than the test set.

We have trained a logistic regression classifier and planned to make predictions according to: Predict y=1 if he (x) ≥ threshold Predict y=0 if he (x) < threshold For different threshold values, we obtain different values of precision (P) and recall (R). Which of the following is a reasonable way to pick the threshold value?
Transcribed Image Text:We have trained a logistic regression classifier and planned to make predictions according to: Predict y=1 if he (x) ≥ threshold Predict y=0 if he (x) < threshold For different threshold values, we obtain different values of precision (P) and recall (R). Which of the following is a reasonable way to pick the threshold value?
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