title: Regression - PCA - What to do with variables?
body: <p>I am trying on a regression model with 44 variables.
  Executing PCA due to multicollinearity, I receive 6 principal components.
  I am using Leave-one-out cross-validation.</p>
  <p>Unfortuneately, due to PCA and its &quot;Measure of sample adequacy&quot;, which should be &gt;0.5 for all variables in PCA, I have to exclude some variables.</p>
  <p>Is this the variable/feature selection part of PCA?
  Is it correct to say, that those variables aren't required to make a good prediction from these variables?</p>
  <p>Thanks.</p>