如何构建和拆分此数据集？

import numpy as np
from sklearn.model_selection import train_test_split

# 假设我们有一个特征矩阵X和一个标签向量y
X = np.array([[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]])
y = np.array([0, 1, 0, 1, 0])

# 首先，将数据集拆分为训练集和临时集（用于进一步拆分为验证集和测试集）
X_train_temp, X_test, y_train_temp, y_test = train_test_split(X, y, test_size=0.3, random_state=42)

# 然后，将临时集拆分为训练集和验证集
X_train, X_val, y_train, y_val = train_test_split(X_train_temp, y_train_temp, test_size=0.25, random_state=42)

print("训练集特征:", X_train)
print("训练集标签:", y_train)
print("验证集特征:", X_val)
print("验证集标签:", y_val)
print("测试集特征:", X_test)
print("测试集标签:", y_test)