def test_mean_feature_importance_do_not_collapse(self):
imps = [
pd.DataFrame([4, 3, 2, 1], columns=["importance0"]),
pd.DataFrame([16, 15, 14, 13], columns=["importance1"])
]
exp = pd.concat(imps, axis=1)
pdt.assert_frame_equal(_mean_feature_importance(imps), exp)
def test_mean_feature_importance_1d_arrays(self):
exp = pd.DataFrame([10, 9, 8, 7],
columns=["importance0"],
index=[3, 2, 1, 0])
imps = [
pd.DataFrame([1, 2, 3, 4], columns=["importance0"]),
pd.DataFrame([5, 6, 7, 8], columns=["importance0"]),
pd.DataFrame([9, 10, 11, 12], columns=["importance0"]),
pd.DataFrame([13, 14, 15, 16], columns=["importance0"])
]
pdt.assert_frame_equal(_mean_feature_importance(imps), exp)
def test_mean_feature_importance_different_column_names(self):
exp = pd.DataFrame([[6, 5, 4, 3], [14, 13, 12, 11]],
index=["importance0", "importance1"],
columns=[3, 2, 1, 0]).T
imps = [
pd.DataFrame([1, 2, 3, 4], columns=["importance0"]),
pd.DataFrame([5, 6, 7, 8], columns=["importance0"]),
pd.DataFrame([9, 10, 11, 12], columns=["importance1"]),
pd.DataFrame([13, 14, 15, 16], columns=["importance1"])
]
pdt.assert_frame_equal(_mean_feature_importance(imps), exp)
def test_mean_feature_importance_2d_arrays(self):
exp = pd.DataFrame([[3.5] * 4, [9.5] * 4],
index=["importance0", "importance1"],
columns=[0, 1, 2, 3]).T
imps = [
pd.DataFrame([[6, 5, 4, 3], [14, 13, 12, 11]],
index=["importance0", "importance1"],
columns=[0, 1, 2, 3]).T,
pd.DataFrame([[1, 2, 3, 4], [5, 6, 7, 8]],
index=["importance0", "importance1"],
columns=[0, 1, 2, 3]).T
]
pdt.assert_frame_equal(_mean_feature_importance(imps), exp)
