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Hi, I have created an SVM classifier for 4 different classes. When testing it with my training data (same data used to train the svm) I get very good predictions ~98% correct.

However when using data outside of my training set, even though it looks similar, I get very poor predictions.

Any suggestions on why this is happening ? I've seen mention of "normalization" and read around about it but I don't quite get what it's for. I'm using Hu Moments as features.

Thanks

Hi, I have created an SVM classifier for 4 different classes. When testing it with my training data (same data used to train the svm) I get very good predictions ~98% correct.

However when using data outside of my training set, even though it looks similar, I get very poor predictions.

Any suggestions on why this is happening ? I've seen mention of "normalization" and read around about it but I don't quite get what it's for. I'm using the natural log of Hu Moments as features.

Thanks