XGBoost 错误：“标签的大小必须等于行数”

如何解决XGBoost 错误：“标签的大小必须等于行数”

我正在尝试为音频分类项目构建 XGBoost 分类器模型。首先，我收到错误消息“ValueError: y should be a 1d array,got an array of shape (102,10) 相反。”但是当我尝试“np.ravel(y_train)”来解决这个问题时，我得到了 XGBoost 错误“标签的大小必须等于行数。”正如您在代码下方看到的那样。谁能为我提供有关如何解决此问题的解决方案？

from xgboost import XGBClassifier
from sklearn.model_selection import cross_val_score

model = XGBClassifier()
model.fit(X_train,np.ravel(y_train))
model.evals_result()
score = cross_val_score(model,X_train,y_train,cv=5)
y_pred = model.predict(X_test)

count = 0
for i in range(y_pred.shape[0]):
    if y_pred[i] == y_test[i]:
        count+=1
    
print('Accuracy for model : ' + str((count / y_pred.shape[0]) * 100))`

XGBoostError                              Traceback (most recent call last)
<ipython-input-40-a4ba931a2bc5> in <module>
    4 model = XGBClassifier()
--->6 model.fit(X_train,np.ravel(y_train))
    7 model.evals_result()
    8 score = cross_val_score(model,cv=5)
XGBoostError: [16:42:08] C:/Users/Administrator/workspace/xgboost- 
win64_release_1.4.0/src/data/data.cc:583: Check Failed: labels_.Size() == num_row_ (1020 vs. 102) : 
Size of labels must equal to number of rows.