Support vector machine prediction system

A computer system, comprising:

• one or more computer processors configured to select a kernel and kernel parameters for a first Support Vector Machine (SVM) model comprising SVM support vector number of support vectors, and to test the first SVM model on a feature matrix T to produce false positive (FP) data set and false negative (FN) data set by a computer processor, wherein the feature matrix T includes n feature vectors of length m, wherein n and m are integer numbers,
• wherein the one or more computer processors are configured to produce a feature matrix T_best using the feature matrix T, wherein the feature matrix T_best comprises T_best sample number of sample points,
• wherein the one or more computer processors are configured to check if a ratio (T_best sample number)/(SVM support vector number) is above a threshold for the first SVM model on the feature matrix T_best,
• wherein the one or more computer processors are configured to perform SVM predictions using the first SVM model on the feature matrix T_best if the ratio is above the threshold,
• wherein the one or more computer processors are configured to select a feature vector v from the FN data set to remove from the feature matrix T_best to produce a feature matrix T_v,
• wherein the one or more computer processors are configured to retrain the first SVM model on the feature matrix T_v to produce a second SVM model.