def testSetWeight2(self):
#Try weight = 0 and weight = 1
svc = SvcGS()
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 testSetWeight2(self):
#Try weight = 0 and weight = 1
svc = SvcGS()
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 testGenerateRBFGS(self):
generate = SvcGS.generate()
learner = generate()
learner.learnModel(self.X, self.y)
learner.predict(self.X)
def testGenerateRBFGS(self):
generate = SvcGS.generate()
learner = generate()
learner.learnModel(self.X, self.y)
learner.predict(self.X)
