I want to run logistic regression to predict binary outcome , however I have 300+ independent variable.
I am new in analytics and statistics ,in my opinion first I need to dimension reduction.
I ran PCA in R and I am getting below error "Error in princomp.default(input, scores = TRUE, COR = TRUE) : covariance matrix is not non-negative definite"
I am not able to resolve above error also in terms of approach if anyone can provide guidance that would be good .
- what should I do to reduce number of variables , identifying powerful predictors ...