Cancer Imaging Phenomics Toolkit (CaPTk)  1.6.1
Miscellaneous: Training Module

This applicatiparameterizeachine">Support Vector Machineparameterize

REQUIREMENTS: Input features file (CSV) and a target label file (CSV).


  1. Launch the application from "Applications" -> "Training Module".
  2. Specify the features (.csv) file and the corresponding target (.csv) file.
  3. Specify the kernel of SVM using either of the two radio buttons, number of folds and output directory. Number of folds could be 5 or 10.
  4. Press "Confirm" button.
  5. The model will be developed and saved in the output directory.
  • This application is also available as with a stand-alone CLI for data analysts to build pipelines around, and can run in the following format.
        TrainingModule -f C:/TestFeatures.csv -l C:/TestLabels.csv -o C:/OutputDirectory -c 1 -n 2 -k 40 
    c is the classifier type (-c 1 for Linear SVM, -c 2 for RBF SVM) n is the configuration type (-n 1 for cross-validation, -n 2 for split train-test) k is the # of folds for cross-validation configuration, and size of train dataset for split train-test configuration