文章翻译自Jonathon Shlens的google research,名为A Tutorial on Principal Component Analysis。 首先,说说我怎么看到这个文章的。我最近在读一篇关于主动路噪控制的论文的时候遇到一个疑问。首先需要采集车内噪声(输出)和底盘的18个振动信号(输入),为了实现降低车内噪声的目的,需要振动信号和车内噪声具有较好的相干函数...
希望有一天也能讲到自己写的文章- - 这次的文章是 A Tutorial on Principal Component Analysis(https://arxiv.org/abs/1404.1100),文章讲解了主成分分析(PCA)的动机与方法。如标题所说,这篇文章严格来说并不是一篇论文,更像一篇 PCA 的教程。 本文使用的符号 感觉这篇文章较为不好的一点是,作者使用的符号在...
白话论文：ATutorialonPrincipalComponentAnalysis ⽩话论⽂：ATutorialonPrincipalComponentAnalysis 最近⾃⼰也在阅读⼀些论⽂，发现⼤部分⽂章都没有那么好懂，阅读起来总是需要很多思考和推理的时间。所以想把⾃⼰读过的⽂章都讲⼀讲，记录⼀下⾃⼰思考和推导的过程。希望有⼀天也能讲到...
atutorialonprincipalcomponentanalysis主成分分析教程 系统标签: tutorialprincipalcomponentanalysis教程pca ATutorialonPrincipalComponentAnalysis JonathonShlens ∗ SystemsNeurobiologyLaboratory,SalkInsituteforBiologicalStudies LaJolla,CA92037and InstituteforNonlinearScience,UniversityofCalifornia,SanDiego LaJolla,CA92093-0402...
A Tutorial on Principal Component AnalysisJonathon Shlens ∗Google ResearchMountain View, CA 94043(Dated: April 7, 2014; Version 3.02)Principal component analysis (PCA) is a mainstay of modern data analysis - a black box that is widely usedbut (sometimes) poorly understood. The goal of this...
参考,A Tutorial on Principal Component Analysis, Jonathon Shlens 主成分分析基于, 在现实中,对于高维的数据,其中有很多维都是扰动噪音,或有些维是冗余的,对描述数据特征没有作用 比如我们在描述汽车速度的时候,用不同的单位mph or kph作为两维,其实只需要其中一维即可 ...
A Tutorial on Principal Component Analysis Principal component analysis (PCA) is a mainstay of modern data analysis - a black box that is widely used but (sometimes) poorly understood. The goal of t... AA Farag 被引量: 541发表: 2009年 Multivariate data analysis in pharmaceutics: A tutorial...
白话论文:A Tutorial on Principal Component Analysis 最近自己也在阅读一些论文,发现大部分文章都没有那么好懂,阅读起来总是需要很多思考和推理的时间。所以想把自己读过的文章都讲一讲,记录一下自己思考和推导的过程。希望有一天也能讲到自己写的文章- - 这次的文章是 A Tutorial on Principal Component Analysis(...
Intuitively, Principal Component Analysis can supply the user with a lower-dimensional picture, a projection or "shadow" of this object when viewed from its most informative viewpoint. ` Image Source: Machine Learning Lectures by Prof. Andrew NG at Stanford University ...
Principal Components Analysis (PCA) is a technique that finds underlying variables (known asprincipal components) that best differentiate your data points. Principal components are dimensions along which your data points are most spread out: A principal component can be expressed by one or more existi...