def split_data(X, y): X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42) return X_train, X_test, y_train, y_test
时间: 2023-07-20 08:30:04 浏览: 36
这是一个Python函数,用于将数据集X和标签y划分为训练集和测试集。函数使用train_test_split模块,将数据集划分为75%的训练集和25%的测试集,并使用随机种子保证划分结果的可重复性。函数返回四个变量:训练集数据X_train、测试集数据X_test、训练集标签y_train、测试集标签y_test。
相关问题
def split_data(): test_size = float(entry.get()) X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=0) huafen=(f'X_train: {X_train}, X_test: {X_test}, y_train: {y_train}, y_test: {y_test}') a6=Text(root) a6.place(x=600, y=100,height=100,width=500) a6.insert(END, huafen)怎么把划分好的比例弄到函数外面
你可以将X_train、X_test、y_train、y_test作为函数的返回值,然后在函数外面接收这些返回值。具体代码如下所示:
```python
def split_data():
test_size = float(entry.get())
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=0)
return X_train, X_test, y_train, y_test
X_train, X_test, y_train, y_test = split_data()
huafen = f'X_train: {X_train}, X_test: {X_test}, y_train: {y_train}, y_test: {y_test}'
a6 = Text(root)
a6.place(x=600, y=100, height=100, width=500)
a6.insert(END, huafen)
```
这样,划分好的比例就可以在函数外面使用了。
def split_data(): global X_train, X_test, y_train, y_test test_size = float(entry.get()) X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=0) huafen=(f'X_train: {X_train}, X_test: {X_test}, y_train: {y_train}, y_test: {y_test}') a6=Text(root) a6.place(x=600, y=100,height=100,width=500) a6.insert(END, huafen)怎么让X_train, X_test, y_train, y_test 拿到def外面也能用
你可以将split_data函数的返回值设为X_train, X_test, y_train, y_test,然后在函数调用的地方将其保存到全局变量中,这样就可以在函数外部使用了。
例如:
```
def split_data():
test_size = float(entry.get())
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=0)
return X_train, X_test, y_train, y_test
X_train, X_test, y_train, y_test = split_data() # 在函数外部调用split_data函数并保存返回值到全局变量中
```