def test_ecoc_probability():
features,labels = load()
features = features[labels < 5]
labels = labels[labels < 5]
raw = svm.svm_raw(kernel=svm.dot_kernel(), C=1.)
base = ctransforms(raw, svm.svm_sigmoidal_correction())
learner = ecoc_learner(base, probability=True)
model = learner.train(features[::2], labels[::2])
results = list(map(model.apply, features[1::2]))
results = np.array(results)
assert results.shape[1] == len(set(labels))
assert np.mean(results.argmax(1) == labels[1::2]) > .5
def test_ecoc_learner():
base = milk.tests.fast_classifier.fast_classifier()
learner = milk.supervised.multi.ecoc_learner(base)
features, labels = load()
nlabels = len(set(labels))
model = learner.train(features[::2],labels[::2])
testl = np.array(model.apply_many(features[1::2]))
assert np.mean(testl == labels[1::2]) > 1./nlabels
assert testl.min() >= 0
assert testl.max() < nlabels
# This failed at one point:
learner = ecoc_learner(svm.svm_to_binary(svm.svm_raw(kernel=svm.dot_kernel(), C=1.)))
model = learner.train(features[:200], labels[:200])
assert (model is not None)