'Fit linear model with Passive Aggressive algorithm.
Parameters
X : {array-like, sparse matrix}, shape = [n_samples, n_features]
Subset of training data
y : numpy array of shape [n_samples]
Subset of target values
Returns
self : returns an instance of self.'

def partial_fit(self, X, y):

    lr = ('pa1' if (self.loss == 'epsilon_insensitive') else 'pa2')
    return self._partial_fit(X, y, alpha=1.0, C=self.C, loss='epsilon_insensitive', learning_rate=lr, max_iter=1, sample_weight=None, coef_init=None, intercept_init=None)
