classification problem, use logistic regression, cross validation, test accuracy using R
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Project Budget$30 - $250 USD
Completed In1 day
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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