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
