我正在尝试使用装袋算法为LasVegasTripAdvisorReviews-Dataset构建模型，遇到了一个错误（多标签和多输出分类不受支持），您能帮我解决这个问题并告诉我如何解决这个错误吗？

此致
附件包含指向拉斯维加斯数据集 LasVegasTripAdvisorReviews-Dataset的链接

# 用于分类的投票集成
import pandas
from sklearn import model_selection
from sklearn.linear_model import LogisticRegression   
from sklearn.tree import DecisionTreeClassifier
from sklearn.svm import SVC
from sklearn.ensemble import VotingClassifier,GradientBoostingClassifier,AdaBoostClassifier,RandomForestClassifier
url = "h:/LasVegasTripAdvisorReviews-Dataset.csv"
names = ['User country','Nr. reviews','Nr. hotel reviews','Helpful votes','Period of stay','Traveler type','Pool','Gym','Tennis court','Spa','Casino','Free internet','Hotel name','Hotel stars','Nr. rooms','User continent','Member years','Review month','Review weekday','Score']
dataframe = pandas.read_csv(url, names=names)
array = dataframe.values
X = array[:,:]
Y = array[:,:]
seed = 7
kfold = model_selection.KFold(n_splits=10, random_state=seed)
# 创建子模型
estimators = []
model1 = AdaBoostClassifier()
estimators.append(('AdaBoost', model1))
model2 = GradientBoostingClassifier()
estimators.append(('GradientBoosting', model2))
model3 = RandomForestClassifier()
estimators.append(('RandomForest', model3))
# 创建集成模型
ensemble = VotingClassifier(estimators)
results = model_selection.cross_val_score(ensemble, X, Y, cv=kfold)
print(results.mean())

堆栈跟踪：

NotImplementedError                       Traceback (most recent call last)
<ipython-input-9-bda887b4022f> in <module>
    27 # create the ensemble model
    28 ensemble = VotingClassifier(estimators)
---> 29 results = model_selection.cross_val_score(ensemble, X, Y, cv=kfold)
    30 print(results.mean())
/usr/local/lib/python3.5/dist-packages/sklearn/model_selection/_validation.py in cross_val_score(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, error_score)
    400                                 fit_params=fit_params,
    401                                 pre_dispatch=pre_dispatch,
--> 402                                 error_score=error_score)
    403     return cv_results['test_score']
    404
......NotImplementedError: Multilabel and multi-output classification is not supported.

回答：

您有以下代码行：

    X = array[:,:]
    Y = array[:,:]

这意味着您的特征矩阵（X）和目标向量（Y）是相同的。

您需要仅选择一列作为您的Y。

例如，假设您希望最后一列作为Y。

那么，您应该将上述代码行更改为如下：

X = values[:,:-1]
Y = values[:,-1:]

这应该能解决您遇到的错误。您遇到的错误基本上意味着：我不支持Y中超过一列。