def create_valid(self, data, label=None, weight=None, group=None,
                     init_score=None, silent=False, params=None):
        """Create validation data align with current Dataset.

        Parameters
        ----------
        data : string, numpy array, pandas DataFrame, H2O DataTable's Frame, scipy.sparse or list of numpy arrays
            Data source of Dataset.
            If string, it represents the path to txt file.
        label : list, numpy 1-D array, pandas Series / one-column DataFrame or None, optional (default=None)
            Label of the data.
        weight : list, numpy 1-D array, pandas Series or None, optional (default=None)
            Weight for each instance.
        group : list, numpy 1-D array, pandas Series or None, optional (default=None)
            Group/query size for Dataset.
        init_score : list, numpy 1-D array, pandas Series or None, optional (default=None)
            Init score for Dataset.
        silent : bool, optional (default=False)
            Whether to print messages during construction.
        params : dict or None, optional (default=None)
            Other parameters for validation Dataset.

        Returns
        -------
        valid : Dataset
            Validation Dataset with reference to self.
        """
        ret = Dataset(data, label=label, reference=self,
                      weight=weight, group=group, init_score=init_score,
                      silent=silent, params=params, free_raw_data=self.free_raw_data)
        ret._predictor = self._predictor
        ret.pandas_categorical = self.pandas_categorical
        return ret
Create validation data align with current Dataset.

        Parameters
        ----------
        data : string, numpy array, pandas DataFrame, H2O DataTable's Frame, scipy.sparse or list of numpy arrays
            Data source of Dataset.
            If string, it represents the path to txt file.
        label : list, numpy 1-D array, pandas Series / one-column DataFrame or None, optional (default=None)
            Label of the data.
        weight : list, numpy 1-D array, pandas Series or None, optional (default=None)
            Weight for each instance.
        group : list, numpy 1-D array, pandas Series or None, optional (default=None)
            Group/query size for Dataset.
        init_score : list, numpy 1-D array, pandas Series or None, optional (default=None)
            Init score for Dataset.
        silent : bool, optional (default=False)
            Whether to print messages during construction.
        params : dict or None, optional (default=None)
            Other parameters for validation Dataset.

        Returns
        -------
        valid : Dataset
            Validation Dataset with reference to self.