你好，我想在蘑菇数据集上使用一个简单的 AdaBoostClassifier，数据集看起来像这样：

target  cap-shape  cap-surface  cap-color  bruises  odor  \3059       0          2            3          2        1     5   1953       0          5            0          3        1     5   1246       0          2            2          3        0     5   5373       1          5            2          8        1     2   413        0          5            3          9        1     3   

…

使用以下代码：

from sklearn.ensemble import AdaBoostClassifierfrom sklearn.preprocessing import LabelEncoderimport pandas as pddataset = pd.read_csv('data\mushroom.csv',header=None)dataset = dataset.sample(frac=1)dataset.columns = ['target','cap-shape','cap-surface','cap-color','bruises','odor','gill-attachment','gill-spacing',             'gill-size','gill-color','stalk-shape','stalk-root','stalk-surface-above-ring','stalk-surface-below-ring','stalk-color-above-ring',             'stalk-color-below-ring','veil-type','veil-color','ring-number','ring-type','spore-print-color','population',             'habitat']for label in dataset.columns:    dataset[label] = LabelEncoder().fit(dataset[label]).transform(dataset[label])X = dataset.drop(['target'],axis=1)Y = dataset['target']AdaBoost = AdaBoostClassifier(base_estimator='DecisionTreeClassifier',n_estimators=400,learning_rate=0.01,algorithm='SAMME')AdaBoost.fit(X,Y)prediction = AdaBoost.score(Y)print(prediction)

但这返回给我的是：

—> 15 AdaBoost.fit(X,Y)

AttributeError: ‘str’ 对象没有属性 ‘fit’

回答：

我已经找到了问题所在。我将 base_estimator 设置为 ‘DecisionTreeClassifier’，这是一个字符串，因此没有 fit() 方法。而 AdaBoost 并不是一个字符串。

from sklearn.ensemble import AdaBoostClassifierfrom sklearn.preprocessing import LabelEncoderfor label in dataset.columns:    dataset[label] = LabelEncoder().fit(dataset[label]).transform(dataset[label])X = dataset.drop(['target'],axis=1)Y = dataset['target']AdaBoost = AdaBoostClassifier(n_estimators=400,learning_rate=0.01,algorithm='SAMME')AdaBoost.fit(X,Y)prediction = AdaBoost.score(X,Y)print(prediction)

0.9182668636139832