#Feature selection
    forest = ExtraTreesClassifier(n_estimators=250, random_state=0)
    forest.fit(studentData, finalGradeSeries)
    importances = forest.feature_importances_

    test = np.argsort(importances)
    print(test)


    listToRemove=[test[0]]
    accList=[]
    for i in range(0,29):
        trainingCopy = np.delete(studentData,listToRemove,axis=1)
        scores = model_selection.cross_val_score(classifier,trainingCopy,finalGradeSeries,cv=10)
        print("SVC:",scores.mean(),"after feature",test[i],"removed")
        accList.append(scores.mean())
        listToRemove.append(test[i+1])



    plt.plot(range(0,29),accList)
    plt.show()