ModuleNotFoundError: No module named 'sklearn.cross_validation' что тут не так?

Question

[Руслан]

Пытаюсь запустить данный

код

import pandas
import sklearn
import numpy as np
import pandas as pd
from sklearn.cross_validation import KFold
from sklearn.neighbors import KNeighborsClassifier
from time import time as t
from  pandas import DataFrame
import sys
sys.path.append("..")
 
 
data = pd.read_csv('D:/wine.csv')
 
def crossVal(estimator, X, y, cv):
    result_accracy_list = []
    for train_index, test_index in cv:
        estimator.fit(X.iloc[train_index], 
                      y.iloc[train_index])
        rpesult_accracy_list.apend(np.average(np.array(estimator.predict(X.iloc[test_index]) == np.array(y.iloc[test_index]))))
    return pd.Series(result_accracy_list)
    
from sklearn.cross_validation import KFold #классификатор
kfold = KFold(n = len(data),     #кол-во строк
              n_folds = 5,       #кроссвалидации по 5 блокам
              shuffle = True,    #перемешивает выборку перед формированием блоков
              random_state = 42) #генератор KFold с фиксированным параметром
 
              
from sklearn.neighbors import KNeighborsClassifier #один из алгоритмов классификации
from sklearn.cross_validation import cross_val_score 
 
accuracies_dict = {} 
for k in range(1, 50 + 1):
    classifier = KNeighborsClassifier(n_neighbors = k) 
    #scores = cross_val_score(classifier, data.drop(['Class'], axis = 1), data['Class'], scoring = 'accuracy', cv = kfold)
    scores = crossVal(estimator = classifier, 
                               X = data.drop(['Class'], axis = 1),
                               y = data['Class'],
                               cv = kfold)
    accuracies_dict[k] = scores.mean()
 
optimal_k = sorted(accuracies_dict, key = accuracies_dict.get, reverse = True)[0]
print('optimal k: (', optimal_k, ', %.4f' %accuracies_dict[k], ')')
 
from sklearn.preprocessing import scale
scaled_data = scale(data.drop(['Class'], axis = 1))
 
scaled_accuracies_dict = {}
for k in range(1, 50 + 1):
    classifier = KNeighborsClassifier(n_neighbors=k)
    #scores = cross_val_score(classifier, scaled_data, data['Class'], scoring = 'accuracy', cv = kfold)
    scores = crossVal(estimator = classifier, X = pd.DataFrame(scaled_data), y = data['Class'], cv = kfold)
    scaled_accuracies_dict[k] = scores.mean()
    
optimal_k = sorted(scaled_accuracies_dict, key = scaled_accuracies_dict.get, reverse = True)[0]
print('optimal k ater scaling: (', optimal_k, ', %.4f' %scaled_accuracies_dict[k], ')')#после масштабирования
webowl

И выходит ошибка что модуля нет, почему?

Traceback (most recent call last):

  File "C:\forPythonProjects\Sarieva\twine.py", line 5, in <module>
    from sklearn.cross_validation import KFold

ModuleNotFoundError: No module named 'sklearn.cross_validation'