SVM question
Georges Orlowski wrote:
I'm running SVM from e1071 package on a data with ~150 columns (variables) and 50000 lines of data (it takes a bit of time) for radial kernel for different gamma and cost values. I get a very large models with at least 30000 vectors and the prediction I get is not the best one. What does it mean and what could I do to ameliorate my model ?
Do you mean 30000 *support vectors* in 50000 observations? So you are heavily overfitting. Try to tune the svm better. Uwe Ligges
Jerzy Orlowski
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