def __init__(self, trainer=svr.LinearSVR(), error_fx=sklm.r2_score): #super(RegressionMeasure, self).__init__() Measure.__init__(self) self.trainer = trainer self.fx = error_fx self.mse = sklm.mean_squared_error
def __init__(self, p=0.05): Measure.__init__(self) #self.space = 'targets' self.p = p
def __init__(self): Measure.__init__(self) self.params = dict()
def train(self, ds): Measure.train(self, ds) self.trainer.fit(ds.samples, ds.targets)
def train(self, ds): Measure.train(self, ds) self.trainer.transform(ds.samples, ds.targets)