专栏名称: 机器学习研究会

机器学习研究会是北京大学大数据与机器学习创新中心旗下的学生组织，旨在构建一个机器学习从事者交流的平台。除了及时分享领域资讯外，协会还会举办各种业界巨头/学术神牛讲座、学术大牛沙龙分享会、real data 创新竞赛等活动。

【学习】(Python/R)SVM及调参教程

机器学习研究会 · 公众号 · AI · 2017-02-21 18:48

正文

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摘要

转自：爱可可-爱生活

Introduction

Data classification is a very important task in machine learning. Support Vector Machines (SVMs) are widely applied in the field of pattern classifications and nonlinear regressions. The original form of the SVM algorithm was introduced by Vladimir N. Vapnik and Alexey Ya. Chervonenkis in 1963. Since then, SVMs have been transformed tremendously to be used successfully in many real-world problems such as text (and hypertext) categorization, image classification, bioinformatics (Protein classification, Cancer classification), handwritten character recognition, etc.

What is a Support Vector Machine?
How does it work?
Derivation of SVM Equations
Pros and Cons of SVMs
Python and R implementation

What is a Support Vector Machine(SVM)?

A Support Vector Machine is a supervised machine learning algorithm which can be used for both classification and regression problems. It follows a technique called the kernel trick to transform the data and based on these transformations, it finds an optimal boundary between the possible outputs.

In simple words, it does some extremely complex data transformations to figure out how to separate the data based on the labels or outputs defined.We will be looking only at the SVM classification algorithm in this article.