machine learning - why classification results using SVM is not good in matlab? -

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I have some problem with svm I used svmtrain and svmclassify classification for mass and no mass. I have 40 incorrect positive data and 13 are true positive. When I test it (the data test i have used is = data training) and gives 100% accuracy, but when I test it (data testing i get from data training) data training (tp = 8 FP = 30) and data testing (TP = 5FP = 10). The result gives false data all false positives. Have an idea about this problem? Or because the small number of data testing and training?

It is quite normal that independent test sets can perform poorly, which means that your model Clearly stacks because when you get the training data fits, you get 100%. Try adjusting the SVM model parameters, apply data-preprocessing, especially to reduce your fit in standardization training and (hopefully) your independent test data when two accuracy stops, the model will be valid.

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