'Fit the hierarchical clustering on the data
Parameters
X : array-like, shape = [n_samples, n_features]
The data
Returns
self'

def fit(self, X, y=None, **params):

    X = check_array(X, accept_sparse=['csr', 'csc', 'coo'], ensure_min_features=2, estimator=self)
    return AgglomerativeClustering.fit(self, X.T, **params)
