def fit(self, X, y):
X = normalize(polynomial_features(X, degree=self.degree))
super(ElasticNet, self).fit(X, y)
def predict(self, X):
X = normalize(polynomial_features(X, degree=self.degree))
return super(ElasticNet, self).predict(X)
def predict(self, X):
X = normalize(polynomial_features(X, degree=self.degree))
return super(PolynomialRidgeRegression, self).predict(X)
def fit(self, X, y):
X = normalize(polynomial_features(X, degree=self.degree))
super(PolynomialRidgeRegression, self).fit(X, y)
def predict(self,X):
X = polynomial_features(X,degree=self.degree)
return super(PolynomialRegression,self).predict(X)
def fit(self,X,y):
X = polynomial_features(X,degree=self.degree)
super(PolynomialRegression,self).fit(X,y)
def predict(self,X):
X = normalize(polynomial_features(X,degree=self.degree))
return (LassoRegression,self).predict(X)