我对机器学习还比较新手，过去两天我一直在尝试解决Unknown label type: 'continuous'这个错误。

我的代码：import numpy as np

import pandas as pdfrom sklearn.model_selection import train_test_split  from sklearn.preprocessing import StandardScaler  from sklearn.ensemble import RandomForestClassifier  from sklearn.model_selection import cross_val_score  dataset = pd.read_csv(r'allData.csv', sep=',')  X = dataset.iloc[:, 1:3].values  y = dataset.iloc[:, 4].values  train_features, test_features, train_lables, test_lables = train_test_split(X, y, test_size=10, random_state=10)  feature_scaler = StandardScaler()  train_features = feature_scaler.fit_transform(train_features)  test_features = feature_scaler.transform(test_features)  classifier = RandomForestClassifier(n_estimators=300, random_state=10)  all_accuracies = cross_val_score(estimator=classifier, X=train_features, y=train_lables, cv="warn")  #all_accuracies = cross_val_score(estimator=classifier, X=train_features, y=train_lables, cv=3)#print(all_accuracies)  

错误出现在cross_val_score部分，我不明白为什么会得到Unknown label type: 'continuous'这个错误。

任何帮助都将不胜感激。

如果有帮助的话，我的所有数据都是数值型的，有4列，300行。

回答：

您在使用RandomForestClassifier时，输出是连续的。如果您要解决的问题是回归问题，那么您应该使用RandomForestRegressor。