scikit-learn crash silently on Window11 with conda

### Describe the bug

I run my program but it silently crashed.
I think it's a problem that scikit-learn is incompatible with numpy or scipy in some place.
I will show the environment ,the code and the output. Here is a minimal reproducible example.
In this example，I use some dataset,because if I use make_classification ,it directly crashed and output nothing.

### the  environment
I use conda
following is my code
```
conda create -n PR1 python=3.12
conda install -c conda-forge numpy scipy scikit-learn pandas ucimlrepo
```
version
scikit-learn=1.7.2
scipy=1.16.2
numpy=2.3.3

### code
```
from ucimlrepo import fetch_ucirepo 
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.model_selection import ShuffleSplit
from sklearn.preprocessing import LabelEncoder, StandardScaler

 
connectionist_bench_sonar_mines_vs_rocks = fetch_ucirepo(id=151) 
  
 
X = connectionist_bench_sonar_mines_vs_rocks.data.features 
y = connectionist_bench_sonar_mines_vs_rocks.data.targets 
le = LabelEncoder()
y = le.fit_transform(y.values.ravel())
scaler = StandardScaler()
X = scaler.fit_transform(X) 


shuffle_splitter=ShuffleSplit(n_splits=10, test_size=0.2, random_state=12)

shuffle_model=LinearDiscriminantAnalysis(n_components=None)

shuffle_scores = []

for fold_number, (train_index, test_index) in enumerate(shuffle_splitter.split(X, y),1):
    
    print(f" {fold_number}  ")
    X_train, X_test = X[train_index], X[test_index]
    y_train, y_test = y[train_index], y[test_index]
    shuffle_model.fit(X=X_train,y=y_train)
    score=shuffle_model.score(X=X_test,y=y_test)
    shuffle_scores.append(score)

print(sum(shuffle_scores)/len(shuffle_scores))
```
### output and analysis
```
1 
 ```
irony,it only output "1"
it seems like program crashed in "shuffle_model.fit(X=X_train,y=y_train)"
To be honest，it is not the first time I meet silent crash in scikit-learn
I use AI but it doesn't work.
Any help or insights on what might be causing this would save me and be greatly appreciated. Thank you!


### Steps/Code to Reproduce

from ucimlrepo import fetch_ucirepo 
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.model_selection import ShuffleSplit
from sklearn.preprocessing import LabelEncoder, StandardScaler

 
connectionist_bench_sonar_mines_vs_rocks = fetch_ucirepo(id=151) 
  
 
X = connectionist_bench_sonar_mines_vs_rocks.data.features 
y = connectionist_bench_sonar_mines_vs_rocks.data.targets 
le = LabelEncoder()
y = le.fit_transform(y.values.ravel())
scaler = StandardScaler()
X = scaler.fit_transform(X) 


shuffle_splitter=ShuffleSplit(n_splits=10, test_size=0.2, random_state=12)

shuffle_model=LinearDiscriminantAnalysis(n_components=None)

shuffle_scores = []

for fold_number, (train_index, test_index) in enumerate(shuffle_splitter.split(X, y),1):
    
    print(f" {fold_number}  ")
    X_train, X_test = X[train_index], X[test_index]
    y_train, y_test = y[train_index], y[test_index]
    shuffle_model.fit(X=X_train,y=y_train)
    score=shuffle_model.score(X=X_test,y=y_test)
    shuffle_scores.append(score)

print(sum(shuffle_scores)/len(shuffle_scores))

### Expected Results

an result

### Actual Results

1

### Versions

```shell
scikit-learn=1.7.2
scipy=1.16.2
numpy=2.3.3
```

COMMENT:
I find the reason and solve this problem.
The trick is use pip install numpy,scipy,scikit-learn
don't use conda install
Thanks to everyone,love.

Labels: Bug, Needs Triage