<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Scikit-Learn on gdpark.blog</title><link>https://gdpark.blog/tags/scikit-learn/</link><description>Recent content in Scikit-Learn on gdpark.blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 Nov 2019 00:00:00 +0000</lastBuildDate><atom:link href="https://gdpark.blog/tags/scikit-learn/index.xml" rel="self" type="application/rss+xml"/><item><title>Logistic Regression Part 3 [Machine Learning I Studied #13]</title><link>https://gdpark.blog/posts/machine-learning-13-logistic-regression-part-3/</link><pubDate>Sat, 23 Nov 2019 00:00:00 +0000</pubDate><guid>https://gdpark.blog/posts/machine-learning-13-logistic-regression-part-3/</guid><description>We bend our binary logistic regression into a multi-class classifier using the one-vs-rest trick, then try it out on sklearn&amp;rsquo;s iris dataset.</description></item></channel></rss>