bench_20newsgroups.py

### Describe the bug

```shell
usage: ipykernel_launcher.py [-h] -e
                             {dummy,random_forest,extra_trees,logistic_regression,naive_bayes,adaboost}
                             [{dummy,random_forest,extra_trees,logistic_regression,naive_bayes,adaboost} ...]
ipykernel_launcher.py: error: the following arguments are required: -e/--estimators
```

An exception has occurred, use %tb to see the full traceback.

### Steps/Code to Reproduce

```python
import argparse
from time import time

import numpy as np

from sklearn.datasets import fetch_20newsgroups_vectorized
from sklearn.dummy import DummyClassifier
from sklearn.ensemble import (
    AdaBoostClassifier,
    ExtraTreesClassifier,
    RandomForestClassifier,
)
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
from sklearn.naive_bayes import MultinomialNB
from sklearn.utils.validation import check_array

ESTIMATORS = {
    "dummy": DummyClassifier(),
    "random_forest": RandomForestClassifier(max_features="sqrt", min_samples_split=10),
    "extra_trees": ExtraTreesClassifier(max_features="sqrt", min_samples_split=10),
    "logistic_regression": LogisticRegression(),
    "naive_bayes": MultinomialNB(),
    "adaboost": AdaBoostClassifier(n_estimators=10),
}

parser = argparse.ArgumentParser()
    parser.add_argument(
        "-e", "--estimators", nargs="+", required=True, choices=ESTIMATORS
    )
    args = vars(parser.parse_args())
```

### Expected Results

I dont Know

### Actual Results

```
usage: ipykernel_launcher.py [-h] -e
                             {dummy,random_forest,extra_trees,logistic_regression,naive_bayes,adaboost}
                             [{dummy,random_forest,extra_trees,logistic_regression,naive_bayes,adaboost} ...]
ipykernel_launcher.py: error: the following arguments are required: -e/--estimators
An exception has occurred, use %tb to see the full traceback.

SystemExit: 2
```


### Versions

```shell
System:
    python: 3.11.3 (main, Apr 19 2023, 23:54:32) [GCC 11.2.0]
executable: /home/narendra/anaconda3/bin/python
   machine: Linux-5.15.0-78-generic-x86_64-with-glibc2.35

Python dependencies:
      sklearn: 1.2.2
          pip: 23.1.2
   setuptools: 67.8.0
        numpy: 1.24.3
        scipy: 1.10.1
       Cython: None
       pandas: 1.5.3
   matplotlib: 3.7.1
       joblib: 1.2.0
threadpoolctl: 2.2.0

Built with OpenMP: True

threadpoolctl info:
       filepath: /home/narendra/anaconda3/lib/libmkl_rt.so.2
         prefix: libmkl_rt
       user_api: blas
   internal_api: mkl
        version: 2023.1-Product
    num_threads: 2
threading_layer: intel

       filepath: /home/narendra/anaconda3/lib/libiomp5.so
         prefix: libiomp
       user_api: openmp
   internal_api: openmp
        version: None
    num_threads: 4

       filepath: /home/narendra/anaconda3/lib/libgomp.so.1.0.0
         prefix: libgomp
       user_api: openmp
   internal_api: openmp
        version: None
    num_threads: 4
```

COMMENT:
It indicates that you need to run this benchmark via the command line and provide a `-e` parameter to check which model you are using, e.g.:

```shell
python bench_20newsgroups.py -e dummy
```

```
20 newsgroups
=============
X_train.shape = (11314, 130107)
X_train.format = csc
X_train.dtype = float32
X_train density = 0.001214353154362896
y_train (11314,)
X_test (7532, 130107)
X_test.format = csr
X_test.dtype = float32
y_test (7532,)

Classifier Training
===================
Training dummy ... done

Classification performance:
===========================

Classifier   train-time test-time Accuracy
--------------------------------------------
dummy             0.0005s    0.0010s     0.0530
```

Labels: Bug, Needs Triage