Error: "Boolean array expected for the condition, not float64" during StratifiedK-fold

i’m trying to use the stratifid k- fold for cross validation on my dataset but there is the error "Boolean array expected for the condition, not float64" (in the heading code below). Does anyone know the reason?

This is the code:

import pandas as pd
import numpy as np
from sklearn.model_selection import StratifiedKFold
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score

from imblearn.over_sampling import SMOTE
cleanedDataset = `pd.read_csv("train_numeric_shuffled_50000_cleaned_90.csv")`

#providing input and output features
x=cleanedDataset.drop(['Id','Response'], axis=1)
y=cleanedDataset['Response']

#applico Stratified K-fold con K=4
skf = StratifiedKFold(n_splits=4)

#stampo risultati dei 4 fold
for i, (train_index, test_index) in enumerate(skf.split(x, y)):
        print(f"Fold {i}:")
        print(f"  Train: index={train_index}")
        print(f"  Test:  index={test_index}")

#uso la colonna response come Target
target = cleanedDataset.loc[:,'Response']

#definizione train model
model = LogisticRegression()
def train_model(train, test, fold_no):

    x_train = train[x]
    y_train = train[y]
    x_test = test[x]
    x_test = test[y]
    model.fit(X_train,y_train)
    predictions = model.predict(X_test)
    print('Fold',str(fold_no),'Accuracy:',accuracy_score(y_test,predictions))

#stampo valori accuratezza algoritmo
fold_no =1
for train_index, test_index in skf.split(cleanedDataset, target):
    train = cleanedDataset.loc[train_index,:]
    test = cleanedDataset.loc[test_index,:]
    train_model(train,test,fold_no)
    fold_no += 1

This is the error traceback from the last few line:

 ValueError  Traceback (most recent call last)
    ~AppDataLocalTempipykernel_80041316530102.py in <module>
          4     train = cleanedDataset.loc[train_index,:]
          5     test = cleanedDataset.loc[test_index,:]
    ----> 6     train_model(train,test,fold_no)
          7     fold_no += 1
    
    ~AppDataLocalTempipykernel_80043643313375.py in train_model(train, test, fold_no)
          3 def train_model(train, test, fold_no):
          4 
    ----> 5     X_train = train[x]
          6     y_train = train[y]
          7     X_test = test[x]

~anaconda3libsite-packagespandascoreframe.py in __getitem__(self, key)
   3490         # Do we have a (boolean) DataFrame?
   3491         if isinstance(key, DataFrame):
-> 3492             return self.where(key)
   3493 
   3494         # Do we have a (boolean) 1d indexer?

~anaconda3libsite-packagespandasutil_decorators.py in wrapper(*args, **kwargs)
    309                     stacklevel=stacklevel,
    310                 )
--> 311             return func(*args, **kwargs)
    312 
    313         return wrapper

~anaconda3libsite-packagespandascoreframe.py in where(self, cond, other, inplace, axis, level, errors, try_cast)
  10962         try_cast=lib.no_default,
  10963     ):
> 10964         return super().where(cond, other, inplace, axis, level, errors, try_cast)
  10965 
  10966     @deprecate_nonkeyword_arguments(

~anaconda3libsite-packagespandascoregeneric.py in where(self, cond, other, inplace, axis, level, errors, try_cast)
   9313             )
   9314 
-> 9315         return self._where(cond, other, inplace, axis, level, errors=errors)
   9316 
   9317     @doc(

~anaconda3libsite-packagespandascoregeneric.py in _where(self, cond, other, inplace, axis, level, errors)
   9074                 for dt in cond.dtypes:
   9075                     if not is_bool_dtype(dt):
-> 9076                         raise ValueError(msg.format(dtype=dt))
   9077         else:
   9078             # GH#21947 we have an empty DataFrame/Series, could be object-dtype

ValueError: Boolean array expected for the condition, not float64

What i suppose to modify?