哪些分类器提供权重向量? [英] Which classifiers provide weight vector?

问题描述

存在哪些机器学习分类器，它们在学习阶段之后提供权重向量?我了解SVM，逻辑回归，感知器和LDA.还有更多吗?

What machine learning classifiers exists which provide after the learning phase a weight vector? I know about SVM, logistic regression, perceptron and LDA. Are there more?

我的目标是使用这些权重向量绘制重要性图.

My goal is to use these weight vector to draw an importance map.

推荐答案

实际上是任何线性分类器具有设计上的这种特性.

Actually any linear classifier has such a property by design.

据我了解，您想要做的事情就是功能选择，而不会切断最不有用的功能.

As I understand, what you want to do is something like feature selection without cut-off of least useful ones.

请参见本文

Mladenić，D.，Brank，J.，Grobelnik，M.，& Milic-Frayling，N.(2004年， 七月).使用线性分类器权重的特征选择:交互 与分类模型.在第27届年会论文集中 国际ACM SIGIR研究与开发会议 信息检索(第234-241页). ACM.

Mladenić, D., Brank, J., Grobelnik, M., & Milic-Frayling, N. (2004, July). Feature selection using linear classifier weights: interaction with classification models. In Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval (pp. 234-241). ACM.

作者比较了几种选择特征的方法，包括SVM权重的使用，并发现最后一种是最好的.

authors compare several methods for feature selection including usage of SVM weights and find the last to be the best.

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