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	<title>scaling Archives - Petamind</title>
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		<title>Feature Engineering FundamentalS</title>
		<link>https://petaminds.com/feature-engineering-fundamentals/</link>
					<comments>https://petaminds.com/feature-engineering-fundamentals/#respond</comments>
		
		<dc:creator><![CDATA[Tung Nguyen]]></dc:creator>
		<pubDate>Tue, 22 Sep 2020 11:20:23 +0000</pubDate>
				<category><![CDATA[data science]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[engineering]]></category>
		<category><![CDATA[feature]]></category>
		<category><![CDATA[one-hot]]></category>
		<category><![CDATA[research]]></category>
		<category><![CDATA[scaling]]></category>
		<category><![CDATA[split]]></category>
		<category><![CDATA[standardization]]></category>
		<guid isPermaLink="false">https://petaminds.com/?p=2714</guid>

					<description><![CDATA[<p>The features you use influence more than everything else the result. No algorithm alone, to my knowledge, can supplement the information gain given by correct&#160;feature engineering. — Luca Massaron What is a feature and why we need engineering of it? Basically, all machine learning algorithms use some input data to create outputs. This input data [&#8230;]</p>
<p>The post <a href="https://petaminds.com/feature-engineering-fundamentals/">Feature Engineering FundamentalS</a> appeared first on <a href="https://petaminds.com">Petamind</a>.</p>
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