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如何在 n=4 处显示 Kfolds 数组中的所有 4 个拆分?

[英]How to display all 4 splits in a array for Kfolds at n=4?

此列表中的每个元组应包含一个 train_indices 列表和一个 test_indices 列表,其中包含该特定第 K 次拆分的训练/测试数据点索引。

以下是我们希望通过数据集实现的目标:

data_indices = [(list_of_train_indices_for_split_1, list_of_test_indices_for_split_1)
              (list_of_train_indices_for_split_2, list_of_test_indices_for_split_2)
              (list_of_train_indices_for_split_3, list_of_test_indices_for_split_3)
                                               ...
                                               ...
              (list_of_train_indices_for_split_K, list_of_test_indices_for_split_K)]

这是我目前的 function:

 def sklearn_kfold_split(data,K):

    kf = KFold(n_splits = K, shuffle = False, random_state = None)
    result = next(kf.split(data), None)

    return [result]

function的output:

      sklearn_kfold_split(data,4)

 [(array([15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
     32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48,
     49, 50, 51, 52, 53, 54, 55, 56, 57]),
  array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14]))]

我不确定我应该添加或更改什么来获得下面的 output:

 [(array([15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
     32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48,
     49, 50, 51, 52, 53, 54, 55, 56, 57]),
  array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14])),
 (array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 30, 31,
     32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48,
     49, 50, 51, 52, 53, 54, 55, 56, 57]),
  array([15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])),
 (array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
     17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 44, 45, 46, 47,
     48, 49, 50, 51, 52, 53, 54, 55, 56, 57]),
  array([30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43])),
 (array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
     17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,
     34, 35, 36, 37, 38, 39, 40, 41, 42, 43]),
  array([44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57]))]

关于我可以在 function 上进行更改的任何帮助或建议

解决此问题的最简单方法是使用列表推导来遍历KFold.split的结果:

import pandas as pd
from sklearn.model_selection import KFold

def sklearn_kfold_split(data, K):
    kf = KFold(n_splits=K, shuffle=False, random_state=None)
    result = [(train_index, test_index) for train_index, test_index in kf.split(data)]
    return result


data = list(range(12))
K = 4
sklearn_kfold_split(data_indices, K)

Output:

[(array([ 3,  4,  5,  6,  7,  8,  9, 10, 11]), array([0, 1, 2])),
 (array([ 0,  1,  2,  6,  7,  8,  9, 10, 11]), array([3, 4, 5])),
 (array([ 0,  1,  2,  3,  4,  5,  9, 10, 11]), array([6, 7, 8])),
 (array([0, 1, 2, 3, 4, 5, 6, 7, 8]), array([ 9, 10, 11]))]

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