3842da1683baeeb426ca84d04617f84d99f8183c,autosklearn/metalearning/metafeatures/metafeatures.py,NumberOfInstancesWithMissingValues,_calculate_sparse,#NumberOfInstancesWithMissingValues#Any#Any#Any#,190

Before Change

            num_missing = [
                np.sum(missing.data[missing.indptr[i]:missing.indptr[i + 1]])
                                    for i in range(missing.shape[0])]
        elif scipy.sparse.isspmatrix_csc(missing):
            num_missing = [np.sum(missing.data[missing.indices == i])
                           for i in range(missing.shape[0])]

        return float(np.sum([1 if num > 0 else 0 for num in num_missing]))

After Change

    def _calculate_sparse(self, X, y, categorical):
        missing = helper_functions.get_value("MissingValues")
        new_missing = missing.tocsr()
        num_missing = [
            np.sum(new_missing.data[new_missing.indptr[i]:new_missing.indptr[i + 1]])
                                for i in range(new_missing.shape[0])]

Instances