def test_bucket_binning(self):
bin_param = FeatureBinningParam(bin_num=self.bin_num,
bin_indexes=self.cols)
bucket_bin = BucketBinning(bin_param)
split_points = bucket_bin.fit_split_points(self.table)
split_point = list(split_points.values())[0]
for kth, s_p in enumerate(split_point):
expect_s_p = (self.data_num - 1) / self.bin_num * (kth + 1)
self.assertEqual(s_p, expect_s_p)
bucket_bin.cal_local_iv(self.table)
for col_name, iv_attr in bucket_bin.bin_results.all_cols_results.items(
):
# print('col_name: {}, iv: {}, woe_array: {}'.format(col_name, iv_attr.iv, iv_attr.woe_array))
assert abs(iv_attr.iv - 0.00364386529386804) < 1e-6
def test_bucket_binning(self):
bin_param = FeatureBinningParam(bin_num=self.bin_num, cols=self.cols)
bucket_bin = BucketBinning(bin_param)
split_points = bucket_bin.fit_split_points(self.table)
split_point = list(split_points.values())[0]
for kth, s_p in enumerate(split_point):
expect_s_p = (self.data_num - 1) / self.bin_num * (kth + 1)
self.assertEqual(s_p, expect_s_p)
iv_attrs = bucket_bin.cal_local_iv(self.table)
for col_name, iv_attr in iv_attrs.items():
print('col_name: {}, iv: {}, woe_array: {}'.format(
col_name, iv_attr.iv, iv_attr.woe_array))