Cannot import cross_validation

### Describe the bug

For about a week now, I've tried various things to get cross_validation to import and run in my code, but it appears to be missing from my installation of scikit-learn. I went back and forth with PyCharm, and we confirmed (as best as we can) that it's not PyCharm's issue.

### Steps/Code to Reproduce

```from sklearn.ensemble import ExtraTreesClassifier
from sklearn.feature_selection import SelectFromModel
#from sklearn.model_selection import train_test_split
from sklearn.model_selection import train_test_split
from sklearn.model_selection import cross_validation
                                    # Cross validation is mentioned as one of the newer improvements on
                                    # data mining techniques for cybersecurity on p. 49 of
                                    # "Data Mining and Machine Learning for Cybersecurity" by Du and Dua.


data_in = malData.drop(['Name', 'md5', 'legitimate'], axis=1).values
labels = malData['legitimate'].values
extratrees = ExtraTreesClassifier().fit(data_in, labels)
select = SelectFromModel(extratrees, prefit=True)
data_in_new = select.transform(data_in)
print(data_in.shape, data_in_new.shape)

import numpy as np
features = data_in_new.shape[1] # features = variables = columns
importances = extratrees.feature_importances_
indices = np.argsort(importances)[::-1] # Sorts the variables in terms of importance

# Prints the variables in descending order of importance. +2 because we eventually remove the first two columns
for f in range(features):
    print("%d"%(f+1), malData.columns[2+indices[f]],importances[indices[f]])

# Training the RandomForestClassifier
from sklearn.ensemble import RandomForestClassifier
legit_train, legit_test, mal_train, mal_test = cross_validation.train_test_split(data_in_new, labels, test_size=0.2)```

### Expected Results

I'm not 100% sure since I was just following a tutorial, but I expected to be able to eventually print the accuracy of an algorithm after using RandomForestClassifier. I had gotten to that point in the code and ran the file, and then I saw that cross_validate was holding up the process.

### Actual Results

line 27, in <module>
    from sklearn.model_selection import cross_validation
ImportError: cannot import name 'cross_validation' from 'sklearn.model_selection'

### Versions

```shell
System:
    python: 3.9.1 (v3.9.1:1e5d33e9b9, Dec  7 2020, 12:10:52)  [Clang 6.0 (clang-600.0.57)]
executable: /usr/local/bin/python3.9
   machine: macOS-10.16-x86_64-i386-64bit

Python dependencies:
      sklearn: 1.1.3
          pip: 20.2.3
   setuptools: 49.2.1
        numpy: 1.23.4
        scipy: 1.9.3
       Cython: None
       pandas: 1.5.1
   matplotlib: None
       joblib: 1.2.0
threadpoolctl: 3.1.0

Built with OpenMP: True
```

COMMENT:
Hi @bjonsson , thanks for reaching out.
There is no `cross_validation` function in scikit-learn (see the [search on the website](https://scikit-learn.org/dev/search.html?q=cross_validation)).
You are probably looking for `cross_validate`.
I'm closing this one. Feel free to follow up with the author of the example.

Labels: Bug, Needs Triage