def __call__(self, clf, t):
alpha1 = clf.l1_ratio * clf.alpha
alpha2 = (1 - clf.l1_ratio) * clf.alpha
_proj_elastic_all(clf.eta, t, clf.g_sum_[0], clf.g_norms_[0],
alpha1, alpha2, 0, clf.coef_[0])
score = clf.score(self.X, self.y)
self.acc.append(score)
def __call__(self, clf, t):
alpha1 = clf.l1_ratio * clf.alpha
alpha2 = (1 - clf.l1_ratio) * clf.alpha
_proj_elastic_all(clf.eta, t, clf.g_sum_[0], clf.g_norms_[0],
alpha1, alpha2, 0, clf.coef_[0])
score = clf.score(self.X, self.y)
self.acc.append(score)
def __call__(self, clf, t=None):
test_time = time.clock()
if hasattr(clf, "_finalize_coef"):
clf._finalize_coef()
if t is not None:
_proj_elastic_all(clf.eta, t, clf.g_sum_[0], clf.g_norms_[0],
alpha1=0, alpha2=clf.alpha, delta=0,
w=clf.coef_[0])
y_pred = clf.decision_function(self.X).ravel()
loss = (np.maximum(1 - self.y * y_pred, 0) ** 2).mean()
coef = clf.coef_.ravel()
regul = 0.5 * clf.alpha * np.dot(coef, coef)
self.obj.append(loss + regul)
self.test_time += time.clock() - test_time
self.times.append(time.clock() - self.start_time - self.test_time)
def __call__(self, clf, t=None):
test_time = time.clock()
if hasattr(clf, "_finalize_coef"):
clf._finalize_coef()
if t is not None:
_proj_elastic_all(clf.eta, t, clf.g_sum_[0], clf.g_norms_[0],
alpha1=0, alpha2=clf.alpha, delta=0,
w=clf.coef_[0])
y_pred = clf.decision_function(self.X).ravel()
loss = (np.maximum(1 - self.y * y_pred, 0) ** 2).mean()
coef = clf.coef_.ravel()
regul = 0.5 * clf.alpha * np.dot(coef, coef)
self.obj.append(loss + regul)
self.test_time += time.clock() - test_time
self.times.append(time.clock() - self.start_time - self.test_time)