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Data Classification: Basic SVM Classifier

Aim:

This example shows how to prepare and use an SVM classifier model.

To get the best results using an SVM classifier, each class should have at least 2 samples.

More information about the usage of this type of classifier can be found in the SVM_Init description.

Input:

An example CSV file with prepared data.

Output:

An image of classification results for a whole problem's space.

Macrofilter Main

Macrofilter TrainModel

Macrofilter CheckDataset

Macrofilter CheckEntireSpace