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	<title>Comments on: Testing &amp; Diagnosing a Text Classification Algorithm</title>
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	<description>Because the world needs another Business Intelligence blog!</description>
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		<title>By: Thinknook &#124; 10 Ways to Improve your Text Classification Algorithm Accuracy and Performance</title>
		<link>http://thinknook.com/testing-diagnosing-a-text-classification-algorithm-2013-01-19/#comment-1230</link>
		<dc:creator><![CDATA[Thinknook &#124; 10 Ways to Improve your Text Classification Algorithm Accuracy and Performance]]></dc:creator>
		<pubDate>Mon, 21 Jan 2013 13:05:54 +0000</pubDate>
		<guid isPermaLink="false">http://thinknook.com/?p=922#comment-1230</guid>
		<description><![CDATA[[...] have written an article that discusses precision and recall in the context of the Confusion Matrix. The idea here is to tweak the system so when it fails, it does so in a manner that is [...]]]></description>
		<content:encoded><![CDATA[<p>[&#8230;] have written an article that discusses precision and recall in the context of the Confusion Matrix. The idea here is to tweak the system so when it fails, it does so in a manner that is [&#8230;]</p>
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		<title>By: Thinknook &#124; Text Classification Threshold Performance Graph</title>
		<link>http://thinknook.com/testing-diagnosing-a-text-classification-algorithm-2013-01-19/#comment-1222</link>
		<dc:creator><![CDATA[Thinknook &#124; Text Classification Threshold Performance Graph]]></dc:creator>
		<pubDate>Sun, 20 Jan 2013 20:21:55 +0000</pubDate>
		<guid isPermaLink="false">http://thinknook.com/?p=922#comment-1222</guid>
		<description><![CDATA[[...] You could extend this solution and assign different threshold based on the classification results, for example you could say that if the returned classification is Art then our threshold is 0.5, but if the returned classification is Business then our threshold should be 0.6 instead, because we know that our Business classification returns a higher level of False Positives (low precision). If you are attempting variable threshold like that I recommend reading the article on the confusion matrix and precision in classification. [...]]]></description>
		<content:encoded><![CDATA[<p>[&#8230;] You could extend this solution and assign different threshold based on the classification results, for example you could say that if the returned classification is Art then our threshold is 0.5, but if the returned classification is Business then our threshold should be 0.6 instead, because we know that our Business classification returns a higher level of False Positives (low precision). If you are attempting variable threshold like that I recommend reading the article on the confusion matrix and precision in classification. [&#8230;]</p>
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