1、代码

n:数据集大小

from sklearn.model_selection import LeaveOneOut
X=np.array([[1,2,3,4],
        [11,12,13,14],
        [21,22,23,24],
        [31,32,33,34]])
y=np.array([1,1,0,0])

lo=LeaveOneOut()
# lo.len(y)
for train_index,test_index in lo.split(X):
    print("Train Index:",train_index)
    print("Test Index:",test_index)
    print("X_train:",X[train_index])
    print("X_test:",X[test_index])
    print("")

2、结果

【out】:

Train Index: [1 2 3]
Test Index: [0]
X_train: [[11 12 13 14]
 [21 22 23 24]
 [31 32 33 34]]
X_test: [[1 2 3 4]]

Train Index: [0 2 3]
Test Index: [1]
X_train: [[ 1  2  3  4]
 [21 22 23 24]
 [31 32 33 34]]
X_test: [[11 12 13 14]]

Train Index: [0 1 3]
Test Index: [2]
X_train: [[ 1  2  3  4]
 [11 12 13 14]
 [31 32 33 34]]
X_test: [[21 22 23 24]]

Train Index: [0 1 2]
Test Index: [3]
X_train: [[ 1  2  3  4]
 [11 12 13 14]
 [21 22 23 24]]
X_test: [[31 32 33 34]]

Logo

DAMO开发者矩阵,由阿里巴巴达摩院和中国互联网协会联合发起,致力于探讨最前沿的技术趋势与应用成果,搭建高质量的交流与分享平台,推动技术创新与产业应用链接,围绕“人工智能与新型计算”构建开放共享的开发者生态。

更多推荐