diff --git a/learnware/market/heterogeneous/organizer.py b/learnware/market/heterogeneous/organizer.py
deleted file mode 100644
index 15e9ea4..0000000
--- a/learnware/market/heterogeneous/organizer.py
+++ /dev/null
@@ -1,97 +0,0 @@
-from typing import List
-
-import numpy as np
-
-from ...learnware import Learnware
-from ..evolve.organizer import EvolvedOrganizer
-
-
-class MappingFunction:
-    def __init__(self) -> None:
-        pass
-
-    def transform(X: np.ndarray) -> np.ndarray:
-        """transform the data in one feature space to another feature space.
-
-        Parameters
-        ----------
-        X : np.ndarray
-            data in one feature space
-
-        Returns
-        -------
-        np.ndarray
-            transformed data in other feature space
-        """
-        pass
-
-
-class HeterogeneousOrganizer(EvolvedOrganizer):
-    """Organize learnwares with heterogeneous feature spaces, organizer version with evolved learnwares"""
-
-    def __init__(self, *args, **kwargs):
-        super(HeterogeneousOrganizer, self).__init__(*args, **kwargs)
-        self.mapping_function_list = {}
-
-    def _mapping_function_list_initialization(self, learnware_list: List[Learnware]):
-        """Initialize mapping functions with all submitted learnwares
-
-        Parameters
-        ----------
-        learnware_list : List[Learnware]
-            list of learnwares
-        """
-        self.mapping_function_list = self.learn_mapping_functions(learnware_list)
-
-    def learn_mapping_functions(self, learnware_list: List[Learnware]) -> List[MappingFunction]:
-        """Use all statistical specifications of submitted learnwares to generate mapping functions from each original feature space to subsapce and vice verse.
-
-        Parameters
-        ----------
-        learnware_list : List[Learnware]
-            list of learnwares
-
-        Returns
-        -------
-        List[MappingFunction]
-            list of mapping functions
-        """
-        pass
-
-    def transform_original_to_subspace(
-        self, original_feature_space_idx: int, original_feature: np.ndarray
-    ) -> np.ndarray:
-        """Transform feature in a original feature space to the subspace.
-
-        Parameters
-        ----------
-        original_feature_space_idx : int
-            index of the original feature space
-        original_feature : np.ndarray
-            data in the original feature space
-
-        Returns
-        -------
-        np.ndarray
-            mapped data in the subspace
-        """
-        pass
-
-    def transform_subspace_to_original(
-        self, original_feature_space_idx: int, subspace_feature: np.ndarray
-    ) -> np.ndarray:
-        """Transform feature in the subspace to a original feature space.
-
-        Parameters
-        ----------
-        original_feature_space_idx : int
-            index of the original feature space
-        subspace_feature : np.ndarray
-            data in the subspace
-
-        Returns
-        -------
-        np.ndarray
-            mapped data in the original feature space
-        """
-        pass