def doModelsScore(self, labeledGroupName):
'''
Print scores for several different classifiers
'''
X, y = self.loadLabeledData(labeledGroupName, classes=self.args.classes)
X = StandardScaler().fit_transform(X)
if X.any() and y.any():
for name, clf in list(self.classifiers.items()):
scores = cross_val_score(clf, X, y, cv=5)
print("%-18s accuracy: %0.2f (+/- %0.2f)" % (name, scores.mean(), scores.std() * 2))
else:
raise Exception('No data returned for labeledGroupName = %s' % labeledGroupName)
def doModelsScore(self, labeledGroupName):
'''
Print scores for several different classifiers
'''
X, y = self.loadLabeledData(labeledGroupName, classes=self.args.classes)
X = StandardScaler().fit_transform(X)
if X.any() and y.any():
for name, clf in self.classifiers.iteritems():
scores = cross_val_score(clf, X, y, cv=5)
print("%-18s accuracy: %0.2f (+/- %0.2f)" % (name, scores.mean(), scores.std() * 2))
else:
raise Exception('No data returned for labeledGroupName = %s' % labeledGroupName)
