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classification problem, use logistic regression, cross validation, test accuracy using R

This project was successfully completed by kirkhadley for $155 USD in a day.

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Employer working
Project Budget
$30 - $250 USD
Completed In
1 day
Total Bids
13
Project Description

First, need to split the dataset into training set 60%, validation set 20% and test set 20%.

Then start with 1 most important predictor (predictor 5) model logistic regression, use, validation set to measure error, also do 10 k-fold cross validation to measure error , and use test set to get model accuracy.

I know utilize all predictor in this dataset should get most accuracy and least error. I just need someone to do 1 model, and then I can just use same method to do the rest models.

Be aware the response variable are binary 0 and 1, it is a classification problem.

The dataset is attached

you need to first use

mydata <- [url removed, login to view](mydata)

mydata <- mydata[[url removed, login to view](mydata), ]

to make this data work

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