def test_entire_pipeline():
kernel = Scikit_SVM.getLinearKernel()
clf = Scikit_SVM(kernel)
validator = StratifiedCrossValidator(10,clf)
cm = validator.run()
norm_cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
output_util.plot_confusion_matrix(norm_cm,labels_by_frequency,title='Normalized Confusion Matrix')
def test_cm_plotting():
non_normalized_cm = np.loadtxt('../experiments/dataset1_all_C_0.2_chi2_0.1_cfsn_matrix.txt',np.float32)
num_labels = non_normalized_cm.shape[0]
labels = labels_by_frequency[:num_labels]
cm_normalized = non_normalized_cm.astype('float') / non_normalized_cm.sum(axis=1)[:, np.newaxis]
output_util.plot_confusion_matrix(cm_normalized,labels,title='Normalized Confusion Matrix')