<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Dimensionality Reduction on Infinite Script</title><link>https://www.infinitescript.com/tags/dimensionality-reduction/</link><description>Recent content in Dimensionality Reduction on Infinite Script</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 10 Jan 2016 02:13:13 +0000</lastBuildDate><atom:link href="https://www.infinitescript.com/tags/dimensionality-reduction/index.xml" rel="self" type="application/rss+xml"/><item><title>Random Projection</title><link>https://www.infinitescript.com/2016/01/random-projection/</link><pubDate>Sun, 10 Jan 2016 02:13:13 +0000</pubDate><guid>https://www.infinitescript.com/2016/01/random-projection/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;&#10;&lt;p&gt;In mathematics and statistics, random projection is a technique used to reduce the dimensionality of a set of points which lie in Euclidean space. Random projection methods are known for their simplicity and low error rates compared with other dimensionality-reduction techniques, and experiments show that they preserve pairwise distances well.&lt;/p&gt;&#10;&lt;p&gt;Consider a problem as follows: We have a set of $n$ points in a high-dimensional Euclidean space $\mathbf{R}^d$. We want to project the points onto a space of low dimension $\mathbf{R}^k$ in such a way that pairwise distances of the points are approximately the same as before.&lt;/p&gt;</description></item></channel></rss>