Refactor project structure and add Arff load and test

sample.py

@@ -4,7 +4,6 @@ from fimdlp.cppfimdlp import CFImdlp
 from sklearn.ensemble import RandomForestClassifier
 import numpy as np
 import time
-from math import log2
 
 from scipy.io import arff
 import pandas as pd
@@ -44,65 +43,3 @@ print(test.get_cut_points())
 clf = RandomForestClassifier(random_state=0)
 print(clf.fit(Xt, y).score(Xt, y))
 print(Xt)
-# for proposal in [True, False]:
-#     X = data.data
-#     y = data.target
-#     print("*** Proposal: ", proposal)
-#     test = CFImdlp(debug=True, proposal=proposal)
-#     test.fit(X[:, 0], y)
-#     result = test.get_cut_points()
-#     for item in result:
-#         print(
-#             f"Class={item['classNumber']} - ({item['start']:3d}, "
-#             f"{item['end']:3d}) -> ({item['fromValue']:3.1f}, "
-#             f"{item['toValue']:3.1f}]"
-#         )
-#     print(test.get_discretized_values())
-#     print("+" * 40)
-#     X = np.array(
-#         [
-#             [5.1, 3.5, 1.4, 0.2],
-#             [5.2, 3.0, 1.4, 0.2],
-#             [5.3, 3.2, 1.3, 0.2],
-#             [5.4, 3.1, 1.5, 0.2],
-#         ]
-#     )
-#     y = np.array([0, 0, 0, 1])
-#     print(test.fit(X[:, 0], y).transform(X[:, 0]))
-#     result = test.get_cut_points()
-#     for item in result:
-#         print(
-#             f"Class={item['classNumber']} - ({item['start']:3d}, {item['end']:3d})"
-#             f" -> ({item['fromValue']:3.1f}, {item['toValue']:3.1f}]"
-#         )
-#     print("*" * 40)
-# # print(Xs, ys)
-# # print("**********************")
-# # test = [(0, 3), (4, 4), (5, 5), (6, 8), (9, 9)]
-# # print(ys)
-# # for start, end in test:
-# #     print("Testing ", start, end, ys[:end], ys[end:])
-# #     print("Information gain: ", information_gain(ys, ys[:end], ys[end:]))
-# # print(test.transform(X))
-# # print(X)
-# # print(indices)
-# # print(np.array(X)[indices])
-
-
-# # # k = test.cut_points(X[:, 0], y)
-# # # print(k)
-# # # k = test.cut_points_ant(X[:, 0], y)
-# # # print(k)
-# # # test.debug_points(X[:, 0], y)
-# # X = [5.7, 5.3, 5.2, 5.1, 5.0, 5.6, 5.1, 6.0, 5.1, 5.9]
-# # y = [1, 1, 1, 1, 1, 2, 2, 2, 2, 2]
-# # indices = [4, 3, 6, 8, 2, 1, 5, 0, 9, 7]
-# # clf = CFImdlp(debug=True, proposal=False)
-# # clf.fit(X, y)
-# # print(clf.get_cut_points())
-# # y = [1, 1, 1, 1, 1, 2, 2, 2, 2, 2]
-# # # To check
-# # indices2 = np.argsort(X)
-# # Xs = np.array(X)[indices2]
-# # ys = np.array(y)[indices2]
-# kdd_JapaneseVowels