splearn/pipeline.py
def fit(self, Z, **fit_params):
        """Fit all the transforms one after the other and transform the
        data, then fit the transformed data using the final estimator.

        Parameters
        ----------
        Z : ArrayRDD, TupleRDD or DictRDD
            Input data in blocked distributed format.

        Returns
        -------
        self : SparkPipeline
        """
        Zt, fit_params = self._pre_transform(Z, **fit_params)
        self.steps[-1][-1].fit(Zt, **fit_params)
        Zt.unpersist()
        return self
def fit(self, Z, **fit_params):
        """Fit all the transforms one after the other and transform the
        data, then fit the transformed data using the final estimator.

        Parameters
        ----------
        Z : ArrayRDD, TupleRDD or DictRDD
            Input data in blocked distributed format.

        Returns
        -------
        self : SparkPipeline
        """
        Zt, fit_params = self._pre_transform(Z, **fit_params)
        self.steps[-1][-1].fit(Zt, **fit_params)
        Zt.unpersist()
        return self
Fit all the transforms one after the other and transform the
        data, then fit the transformed data using the final estimator.

        Parameters
        ----------
        Z : ArrayRDD, TupleRDD or DictRDD
            Input data in blocked distributed format.

        Returns
        -------
        self : SparkPipeline