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		<title>One-hot encoding matrices demonstration</title>
		<link>https://petaminds.com/one-hot-encoding-matrices-demonstration/</link>
					<comments>https://petaminds.com/one-hot-encoding-matrices-demonstration/#respond</comments>
		
		<dc:creator><![CDATA[Tung Nguyen]]></dc:creator>
		<pubDate>Sun, 29 Dec 2019 02:42:08 +0000</pubDate>
				<category><![CDATA[data science]]></category>
		<category><![CDATA[Project]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[encode]]></category>
		<category><![CDATA[movie lens]]></category>
		<category><![CDATA[one-hot]]></category>
		<category><![CDATA[python]]></category>
		<guid isPermaLink="false">https://petaminds.com/?p=2096</guid>

					<description><![CDATA[<p>This post will demonstrate onehot encoding for a rating matrix, such as movie lens dataset. One-hot encoding Previously, we introduced a quick note for one-hot encoding. It is a representation of categorical variables as binary vectors. It is a group of bits among which the legal combinations of values are only those with a single high (1) [&#8230;]</p>
<p>The post <a href="https://petaminds.com/one-hot-encoding-matrices-demonstration/">One-hot encoding matrices demonstration</a> appeared first on <a href="https://petaminds.com">Petamind</a>.</p>
]]></description>
		
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