我正在尝试使用UCI仓库中的1988年乳腺癌数据集来解决一个分类机器学习问题（https://archive.ics.uci.edu/ml/datasets/Breast+Cancer）。我反复遇到以下错误，尽管并不是每次都出现。有时候算法可以顺利运行到模型训练和预测测试准确率的阶段，有时候在OneHotEncoding阶段失败并显示以下错误：
ohe = OneHotEncoder()ohe.fit(X_train)X_train_encoded = ohe.transform(X_train)X_test_encoded = ohe.transform(X_test)---------------------------------------------------------------------------ValueError Traceback (most recent call last)<ipython-input-5-2cfd638a5b4d> in <module>() 2 ohe.fit(X_train) 3 X_train_encoded = ohe.transform(X_train)----> 4 X_test_encoded = ohe.transform(X_test)1 frames/usr/local/lib/python3.6/dist-packages/sklearn/preprocessing/_encoders.py in _transform(self, X, handle_unknown) 122 msg = ("Found unknown categories {0} in column {1}" 123 " during transform".format(diff, i))--> 124 raise ValueError(msg) 125 else: 126 # Set the problematic rows to an acceptable value andValueError: Found unknown categories ['?'] in column 7 during transform我尝试在Colab和Spyder中运行，但都遇到了相同的问题，不确定哪里出错了。我在分割数据集和编码之前对缺失值进行了填补，但即使我移除了SimpleImputer，仍然会出现错误。
dataset = pd.read_csv('breast-cancer.csv')X = dataset.iloc[:, :-1].valuesy = dataset.iloc[:, -1].valuesfrom sklearn.impute import SimpleImputerimputer = SimpleImputer(missing_values=np.nan, strategy='most_frequent')imputer.fit(X)X_imputed = imputer.transform(X)from sklearn.model_selection import train_test_splitX_train, X_test, y_train, y_test = train_test_split(X_imputed, y, test_size = 0.25)ohe = OneHotEncoder()ohe.fit(X_train)X_train_encoded = ohe.transform(X_train)X_test_encoded = ohe.transform(X_test)<-- Code stops running here -->le = LabelEncoder()le.fit(y_train)y_train_encoded = le.transform(y_train)y_test_encoded = le.transform(y_test)回答：
测试数据可能包含训练数据中不存在的新条目。你可以尝试这样做吗？
ohe = OneHotEncoder(handle_unknown = "ignore")
关于这个参数：在转换过程中，如果存在未知的分类特征，是否抛出错误或忽略（默认是抛出错误）。当此参数设置为’ignore’并且在转换过程中遇到未知类别时，该特征的one-hot编码列将全部为零。
更多信息请查看：
https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html
