Ejemplo n.º 1
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 def predict(self, X):
     X = normalize(polynomial_features(X, degree=self.degree))
     return super(ElasticNet, self).predict(X)
Ejemplo n.º 2
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 def fit(self, X, y):
     X = normalize(polynomial_features(X, degree=self.degree))
     super(ElasticNet, self).fit(X, y)
Ejemplo n.º 3
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 def predict(self, X):
     X = normalize(polynomial_features(X, degree=self.degree))
     return super(PolynomialRidgeRegression, self).predict(X)
Ejemplo n.º 4
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 def fit(self, X, y):
     X = normalize(polynomial_features(X, degree=self.degree))
     super(PolynomialRidgeRegression, self).fit(X, y)
Ejemplo n.º 5
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 def predict(self, X):
     X = polynomial_features(X, degree=self.degree)
     return super(PolynomialRegression, self).predict(X)
Ejemplo n.º 6
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 def fit(self, X, y):
     X = polynomial_features(X, degree=self.degree)
     super(PolynomialRegression, self).fit(X, y)