title: Preprocess data in R
body: <p>Im using R to create logistic regression classifier model.</p>
  
  <p>Here is the code sample:</p>
  
  <pre><code>library(ROCR)
  DATA_SET &lt;- read.csv('E:/1.csv')
  
  classOneCount= 4000
  classZeroCount = 4000
  sample.churn &lt;- sample(which(DATA_SET$Class==1),classOneCount)
  sample.nochurn &lt;- sample(which(DATA_SET$Class==0),classZeroCount )
  
  train.set &lt;- DATA_SET[c(sample.churn,sample.nochurn),]
  test.set  &lt;- DATA_SET[c(-sample.churn,-sample.nochurn),]
  full.logit &lt;- glm(Class~., data = train.set, family = binomial)
  </code></pre>
  
  <p>And it works fine, but I would like to preprocess the data to see if it improves classification model.</p>
  
  <p>What I would like to do would be to divide input vector variables which are continuoes into intervals. Lets say that one variable is height in centimeters in float.</p>
  
  <p>Sample values of height:</p>
  
  <p>183.23
  173.43
  163.53
  153.63
  193.27</p>
  
  <p>and so on, and I would like to split it into lets say 3 different intervals: small, medium, large.</p>
  
  <p>And do it with all variables from my set - there are 32 variables.</p>
  
  <p>What's more I would like to see at the end correlation between value of the variables (this intervals) and classification result class.</p>
  
  <p>Is this clear?</p>
  
  <p>Thank you very much in advance</p>