def testGenerate(self):
generate = SVC.generate()
svc = generate()
svc.learnModel(self.X, self.y)
predY = svc.predict(self.X)
def testGenerate(self):
generate = SVC.generate()
svc = generate()
svc.learnModel(self.X, self.y)
predY = svc.predict(self.X)
def testSetWeight(self):
#Try weight = 0 and weight = 1
svc = SVC()
svc.setWeight(0.0)
svc.learnModel(self.X, self.y)
predY = svc.predict(self.X)
self.assertTrue((predY == numpy.zeros(predY.shape[0])).all())
svc.setWeight(1.0)
svc.learnModel(self.X, self.y)
predY = svc.predict(self.X)
self.assertTrue((predY == numpy.ones(predY.shape[0])).all())
def testSetWeight(self):
#Try weight = 0 and weight = 1
svc = SVC()
svc.setWeight(0.0)
svc.learnModel(self.X, self.y)
predY = svc.predict(self.X)
self.assertTrue((predY == numpy.zeros(predY.shape[0])).all())
svc.setWeight(1.0)
svc.learnModel(self.X, self.y)
predY = svc.predict(self.X)
self.assertTrue((predY == numpy.ones(predY.shape[0])).all())
