Question

我正在唱python库sklearn。我正在使用adaboost分类器，并希望确定哪些功能在分类中最重要。以下是我的代码：

ada =    AdaBoostClassifier(n_estimators=100)
selector = RFECV(ada, step=1, cv=5) 
selector = selector.fit(np.asarray(total_data), np.asarray(target))
selector.support_
print "featue ranking", selector.ranking_

我收到以下错误：

 selector = selector.fit(np.asarray(total_data), np.asarray(target))
  File "C:\Python27\lib\site-packages\sklearn\feature_selection\rfe.py", line 336, in fit
    ranking_ = rfe.fit(X_train, y_train).ranking_
  File "C:\Python27\lib\site-packages\sklearn\feature_selection\rfe.py", line 148, in fit
    if estimator.coef_.ndim > 1:
AttributeError: 'AdaBoostClassifier' object has no attribute 'coef_'

有没有人对它有任何了解，以及如何纠正它。

谢谢！

Answer 1

直接来自RFECV的文档字符串：

Parameters
----------
estimator : object
    A supervised learning estimator with a `fit` method that updates a
    `coef_` attribute that holds the fitted parameters. Important features
    must correspond to high absolute values in the `coef_` array.

    For instance, this is the case for most supervised learning
    algorithms such as Support Vector Classifiers and Generalized
    Linear Models from the `svm` and `linear_model` modules.

换句话说，RFE目前仅针对线性模型实施。您可以将其更改为使用feature_importances_代替coef_并提交补丁，以使其适用于其他模型。

使用adaboost在sklearn中具有重要性

1 个答案: