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	<title>Thinknook &#187; Pearson correlation</title>
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		<title>Generic Trend Classification Engine using Pearson Correlation Coefficient</title>
		<link>http://thinknook.com/approaching-trend-analysis-through-discretization-and-correlation-2012-12-16/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=approaching-trend-analysis-through-discretization-and-correlation</link>
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		<pubDate>Sun, 16 Dec 2012 22:45:38 +0000</pubDate>
		<dc:creator><![CDATA[Links Naji]]></dc:creator>
				<category><![CDATA[Data-Mining]]></category>
		<category><![CDATA[classification]]></category>
		<category><![CDATA[Pearson correlation]]></category>
		<category><![CDATA[social trends]]></category>
		<category><![CDATA[trend analysis]]></category>
		<category><![CDATA[trend classification]]></category>

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		<description><![CDATA[Trend analysis in my experience is generally done through manual (human) review and exploration of data through various BI tools, these tools do a great job by visually highlighting data that can be of interest to the data analyst, and when coupled with data-mining techniques such as clustering and forecasting, it gives us invaluable and [&#8230;]]]></description>
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