'Transform X back to original space.
Parameters
X : array-like, shape (n_samples, n_components)
Returns
X_new : array-like, shape (n_samples, n_features)
References
"Learning to Find Pre-Images", G BakIr et al, 2004.'

def inverse_transform(self, X):

    if (not self.fit_inverse_transform):
        raise NotFittedError('The    fit_inverse_transform    parameter    was    not    set    to    True    when    instantiating    and    hence    the    inverse    transform    is    not    available.')
    K = self._get_kernel(X, self.X_transformed_fit_)
    return np.dot(K, self.dual_coef_)
