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 to binary predictions Observation Y (Model 1) (Model 2) 18 1 1 0263 0 9907 19 0 0 1987 0 3032 40 1 0 1509 0 1989 Accuracy 100 100 Multiple Choice There is no relevant outcome changing to a binary variable By comparing to y , the validation results are not able to be validated By comparing to y , the accuracy of the model is 100 , but can change with a larger validation set By comparing to y , the accuracy of the model is 100 and will not change based on a larger validation set

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Question: In using both the linear probability regression and the logistic regression models for n = 40, the following table is the analysis of the holdout

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 to binary predictions?

Observation	Y	(Model 1)			(Model 2)
18	1		1.0263			0.9907
19	0		0.1987			0.3032
:	:		:			:
40	1		0.1509			0.1989

Accuracy			100	%		100	%

Multiple Choice

There is no relevant outcome changing to a binary variable.
By comparing to y, the validation results are not able to be validated.
By comparing to y, the accuracy of the model is 100%, but can change with a larger validation set.
By comparing to y, the accuracy of the model is 100% and will not change based on a larger validation set.

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