You have a dataset that contains over 150 features.

Step 1: Add a Two-Class Support Vector Machine module to initialize the SVM classifier.

Step 2: Add a dataset to the experiment

Step 3: Add a Split Data module to create training and test dataset.

To generate a set of feature scores requires that you have an already trained model, as well as a test dataset.

Step 4: Add a Permutation Feature Importance module and connect to the trained model and test dataset.

Step 5: Set the Metric for measuring performance property to Classification - Accuracy and then run the experiment.