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5.5. Logistic regression's power lies also in the ability to predict a new observation's class. In order to do that, a cut-off point for the different classes must be established. In this study, an effective treatment of a diseased plant was recorded as (Y = 1) and if not, it was recorded as (Y = 0). The following table shows the predictions by the classification method. True Classification Y = 0 Y = 1 Y = 0 45 10 Predicted Y = 1 17 28 Total 62 38 5.5.1. The above table was created based on the following rule: Predict 1 if în ≥ 0.6 and predict 0 if ft < 0.6, explain this rule.

5.5. Logistic regression's power lies also in the ability to predict a new observation's class. In order to do that, a cut-off point for the different classes must be established. In this study, an effective treatment of a diseased plant was recorded as (Y = 1) and if not, it was recorded as (Y = 0). The following table shows the predictions by the classification method. True Classification Y = 0 Y = 1 Y = 0 45 10 Predicted Y = 1 17 28 Total 62 38 5.5.1. The above table was created based on the following rule: Predict 1 if în ≥ 0.6 and predict 0 if ft < 0.6, explain this rule.

Calculus For The Life Sciences
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 7E
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5.5. Logistic regression's power lies also in the ability to predict a new observation's class. In order to do that, a cut-off point for the different classes must be established. In this study, an effective treatment of a diseased plant was recorded as (Y = 1) and if not, it was recorded as (Y = 0). The following table shows the predictions by the classification method. True Classification Y = 0 Y = 1 Y = 0 45 10 Predicted Ỹ = 1 17 28 Total 62 38 5.5.1. The above table was created based on the following rule: Predict 1 if în ≥ 0.6 and predict 0 if ftn < 0.6, explain this rule.
Transcribed Image Text:5.5. Logistic regression's power lies also in the ability to predict a new observation's class. In order to do that, a cut-off point for the different classes must be established. In this study, an effective treatment of a diseased plant was recorded as (Y = 1) and if not, it was recorded as (Y = 0). The following table shows the predictions by the classification method. True Classification Y = 0 Y = 1 Y = 0 45 10 Predicted Ỹ = 1 17 28 Total 62 38 5.5.1. The above table was created based on the following rule: Predict 1 if în ≥ 0.6 and predict 0 if ftn < 0.6, explain this rule.
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