from pyxvis.io.data import load_features from pyxvis.io.plots import show_confusion_matrix from pyxvis.learning.classifiers import clf_model, define_classifier from pyxvis.learning.classifiers import train_classifier, test_classifier (X, d, Xt, dt) = load_features('../data/F2/F2') # load training and testing data # Classifier definition ss_cl = ['dmin', 'svm-rbf(0.1,1)'] n = len(ss_cl) for k in range(n): (name, params) = clf_model(ss_cl[k]) # function name and parameters clf = define_classifier([name, params]) # classifier definition clf = train_classifier(clf, X, d) # classifier training ds = test_classifier(clf, Xt) # classification of testing show_confusion_matrix(dt, ds, ss_cl[k]) # display confusion matrix
def cross_validation(bcl,X,d,folds): clf = define_classifier(bcl) scores = cross_val_score(clf, X, d, cv=folds) acc = np.mean(scores) return acc