简体   繁体   English

集成分类器是否有可能返回双峰投票?

[英]Is it possible for an ensemble classifier to return bimodal vote?

Knowing fully well that Majority and Plurality voting of ensemble classifiers for prediction of a class label returns the modal prediction by each base classifier, if there's an ensemble of about 4 classifiers and above, is it possible to get a bimodal or trimodal votes?充分了解集成分类器的多数和多个投票以预测类别标签会返回每个基分类器的模态预测,如果有大约 4 个及以上分类器的集成,是否有可能获得双峰或三峰投票? If possible, what will the ensemble return as the predicted class label?如果可能,集成将返回什么作为预测的类标签?

I think it depends on the classifiers that you are trying to ensemble.我认为这取决于您尝试集成的分类器。 If the number of possible labels/classes of each classifier is the same, then 'reducing' a 4 classifiers or above to 2-3 votes can be done using some function/layer.如果每个分类器的可能标签/类的数量相同,则可以使用某些功能/层将 4 个或更多分类器“减少”到 2-3 票。 A common example of a layer you can use to do that is a fully connected neural network layer, which is readily available in many popular libraries (eg Tensorflow, Pytorch, Caffe...)您可以使用的一个常见层示例是完全连接的神经网络层,它可以在许多流行的库(例如 Tensorflow、Pytorch、Caffe...)中轻松获得

In case the types of outputs from each classifier is different, you may need to 'normalize' the classifiers' outputs so that they have the same types and the same ranges of values.如果每个分类器的输出类型不同,您可能需要“标准化”分类器的输出,以便它们具有相同的类型和相同的值范围。 Then these normalized outputs can be used to produce bimodal or trimodal votes, similar to what was explained above.然后这些归一化的输出可用于产生双峰或三峰投票,类似于上面解释的内容。

声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.

 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM