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# Feature Selectionselection and PCA in logistic regression with Rare Events Logitrare events data

I am working on a census-related project where I am interested in assigning to everyone a score that estimates the probability they will have a demographic characteristic of interest. In this case, the demographic characteristic of interest (say, having red hair) is quite rare. (Roughly 15,000 out of 1,000,000 people have red hair.) Though

Though it is easy for me to gather all of the data, due to computational efficiency I am down-sampling my 0s and applying King's and Zeng's corrections from theirKing & Zeng, 2001 paper, Logistic Regression in Rare Events Data.

In an attempt to predict this rare event, I have a couple of questions.

(1) When conducting logistic regression with rare events, how might you suggest executing feature selection?

(2) Is PCA acceptable to use when dealing with logistic regression? With rare event-corrected logistic regression? Do you suggest other methods of ensuring independent variables are orthogonal for this type of model?:

Thanks!

1. When conducting logistic regression with rare events, how might you suggest executing feature selection?

2. Is PCA acceptable to use when dealing with logistic regression? With rare-event-corrected logistic regression? Do you suggest other methods of ensuring independent variables are orthogonal for this type of model?

# Feature Selection and PCA with Rare Events Logit

I am working on a census-related project where I am interested in assigning to everyone a score that estimates the probability they will have a demographic characteristic of interest. In this case, the demographic characteristic of interest (say, having red hair) is quite rare. (Roughly 15,000 out of 1,000,000 people have red hair.) Though it is easy for me to gather all of the data, due to computational efficiency I am down-sampling my 0s and applying King's and Zeng's corrections from their 2001 paper.

In an attempt to predict this rare event, I have a couple of questions.

(1) When conducting logistic regression with rare events, how might you suggest executing feature selection?

(2) Is PCA acceptable to use when dealing with logistic regression? With rare event-corrected logistic regression? Do you suggest other methods of ensuring independent variables are orthogonal for this type of model?

Thanks!

# Feature selection and PCA in logistic regression with rare events data

I am working on a census-related project where I am interested in assigning to everyone a score that estimates the probability they will have a demographic characteristic of interest. In this case, the demographic characteristic of interest (say, having red hair) is quite rare. (Roughly 15,000 out of 1,000,000 people have red hair.)

Though it is easy for me to gather all of the data, due to computational efficiency I am down-sampling my 0s and applying corrections from King & Zeng, 2001, Logistic Regression in Rare Events Data.

In an attempt to predict this rare event, I have a couple of questions:

1. When conducting logistic regression with rare events, how might you suggest executing feature selection?

2. Is PCA acceptable to use when dealing with logistic regression? With rare-event-corrected logistic regression? Do you suggest other methods of ensuring independent variables are orthogonal for this type of model?

1

# Feature Selection and PCA with Rare Events Logit

I am working on a census-related project where I am interested in assigning to everyone a score that estimates the probability they will have a demographic characteristic of interest. In this case, the demographic characteristic of interest (say, having red hair) is quite rare. (Roughly 15,000 out of 1,000,000 people have red hair.) Though it is easy for me to gather all of the data, due to computational efficiency I am down-sampling my 0s and applying King's and Zeng's corrections from their 2001 paper.

In an attempt to predict this rare event, I have a couple of questions.

(1) When conducting logistic regression with rare events, how might you suggest executing feature selection?

(2) Is PCA acceptable to use when dealing with logistic regression? With rare event-corrected logistic regression? Do you suggest other methods of ensuring independent variables are orthogonal for this type of model?

Thanks!