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In Using Both the Linear Probability Regression and the Logistic y^\hat{y}

Question 13

Multiple Choice

In using both the linear probability regression and the logistic regression models for n = 40, the following table is the analysis of the holdout method. Based on the table, what is the impact of changing the y^\hat{y} to binary predictions?  In using both the linear probability regression and the logistic regression models for n = 40, the following table is the analysis of the holdout method. Based on the table, what is the impact of changing the  \hat{y}   to binary predictions?   A)  There is no relevant outcome changing ? to a binary variable. B)  By comparing  \hat{y}   to y, the validation results are not able to be validated. C)  By comparing  \hat{y}   to y, the accuracy of the model is 100%, but can change with a larger validation set. D)  By comparing  \hat{y}   to y, the accuracy of the model is 100% and will not change based on a larger validation set.


A) There is no relevant outcome changing ? to a binary variable.
B) By comparing y^\hat{y} to y, the validation results are not able to be validated.
C) By comparing y^\hat{y} to y, the accuracy of the model is 100%, but can change with a larger validation set.
D) By comparing y^\hat{y} to y, the accuracy of the model is 100% and will not change based on a larger validation set.

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