(self)
return np.asarray(X_train), np.asarray(y_train), np.asarray(self._indexes)
Get training set.

        Returns
        -------
        X_train: list, shape (n_training_examples, n_features)
            The feature matrix of training data.

        y_train: list
            The labels of training data.

        indexes: list
            The indexes of the instances and labels.
            e.g. the first row of X_train is the indexes[0] instance in feature matrix X.
Get training set.
Get training set .
def get_training_data(self):
        """Get training set.

        Returns
        -------
        X_train: list, shape (n_training_examples, n_features)
            The feature matrix of training data.

        y_train: list
            The labels of training data.

        indexes: list
            The indexes of the instances and labels.
            e.g. the first row of X_train is the indexes[0] instance in feature matrix X.
        """
        X_train = []
        y_train = []
        for ind in self._indexes:
            if self._instance_flag:
                X_train.append(self._ind2exa[ind])
            y_train.append(self._ind2label[ind])
        return np.asarray(X_train), np.asarray(y_train), np.asarray(self._indexes)
def get_training_data ( self ) : X_train = [ ] y_train = [ ] for ind in self . _indexes : if self . _instance_flag : X_train . append ( self . _ind2exa [ ind ] ) y_train . append ( self . _ind2label [ ind ] ) return np . asarray ( X_train ) , np . asarray ( y_train ) , np . asarray ( self . _indexes )