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统计学习方法相关算法的matlab实现

于 2022-06-20 发布 文件大小:8.54 kB
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应用背景该文件夹包含模式识别识别的8个程序, 1.Fisher分类算法 2.感知器算法 3.最小二乘算法 4.快速近邻算法 5.K-近邻法 6.剪辑近邻法和压缩近邻法 7.二叉决策树算法 各.m文件均为脚本程序,而非函数,可以很简单的将其改成函数形式 主要考虑到这只是演示,便于傻瓜操作,所以各.m文件均为脚本程序。关键技术main.m:主函数,提供命令行交互操作,即可通过交互查看演示效果,也可单独运行各脚本程序 Fishe.m: Fisher算法 SinglePerceptron.m: 单样本修正感知器算法 Widrow_Hoff.m: 最小二乘法 decisionTree.m: 二叉决策树 KNN.m: K-近邻法 FastNN.m: 快速近邻法 Condensing.m: 剪辑近邻法和压缩近邻法 NNforCondense.m: 唯一的一个函数,供Condensing.m调用

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