Python sklearn LeavePGroupsOut用法及代碼示例

本文簡要介紹python語言中 sklearn.model_selection.LeavePGroupsOut 的用法。

用法:

class sklearn.model_selection.LeavePGroupsOut(n_groups)

將 P 組排除在外cross-validator

提供訓練/測試索引以根據第三方提供的組拆分數據。該組信息可用於將樣本的任意域特定分層編碼為整數。

例如，這些組可以是樣本收集的年份，因此允許針對基於時間的拆分進行交叉驗證。

LeavePGroupsOut 和 LeaveOneGroupOut 之間的區別在於，前者使用分配給 p 不同組值的所有樣本來構建測試集，而後者使用所有分配給相同組的樣本。

在用戶指南中閱讀更多信息。

參數：

n_groups：int

要在測試拆分中遺漏的組數 (p)。

例子：

>>> import numpy as np
>>> from sklearn.model_selection import LeavePGroupsOut
>>> X = np.array([[1, 2], [3, 4], [5, 6]])
>>> y = np.array([1, 2, 1])
>>> groups = np.array([1, 2, 3])
>>> lpgo = LeavePGroupsOut(n_groups=2)
>>> lpgo.get_n_splits(X, y, groups)
3
>>> lpgo.get_n_splits(groups=groups)  # 'groups' is always required
3
>>> print(lpgo)
LeavePGroupsOut(n_groups=2)
>>> for train_index, test_index in lpgo.split(X, y, groups):
...     print("TRAIN:", train_index, "TEST:", test_index)
...     X_train, X_test = X[train_index], X[test_index]
...     y_train, y_test = y[train_index], y[test_index]
...     print(X_train, X_test, y_train, y_test)
TRAIN: [2] TEST: [0 1]
[[5 6]] [[1 2]
 [3 4]] [1] [1 2]
TRAIN: [1] TEST: [0 2]
[[3 4]] [[1 2]
 [5 6]] [2] [1 1]
TRAIN: [0] TEST: [1 2]
[[1 2]] [[3 4]
 [5 6]] [1] [2 1]