An easy-to-follow introduction to support vector machinesThis book provides an in-depth, easy-to-follow introduction to support vector machines drawing only from minimal, carefully motivated technical and mathematical background material. It begins with a cohesive discussion of machine learning and goes on to cover:Knowledge discovery environmentsDescribing data mathematicallyLinear decision surfaces and functionsPerceptron learningMaximum margin classifiersSupport vector machinesElements of statistical learning theoryMulti-class classificationRegression with support vector machinesNovelty detectionComplemented with hands-on exercises, algorithm descriptions, and data sets, Knowledge Discovery with Support Vector Machines is an invaluable textbook for advanced undergraduate and graduate courses.

简单易懂的支持向量机介绍本书提供了一个深入的，简单易懂的支持向量机介绍，仅从最小的，精心设计的技术和数学背景材料绘制。它从机器学习的内聚性讨论开始，接着包括：知识发现环境数学描述数据线性决策面和函数Perceptron learning最大边际分类器支持向量机统计学习理论的要素多类分类支持向量回归机器新颖性检测与实践练习、算法描述和数据集相结合，支持向量机知识发现是高等本科生和研究生课程的宝贵教科书。