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	<title>Thinknook &#187; Classification</title>
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		<title>10 Tips to Improve your Text Classification Algorithm Accuracy and Performance</title>
		<link>http://thinknook.com/10-ways-to-improve-your-classification-algorithm-performance-2013-01-21/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=10-ways-to-improve-your-classification-algorithm-performance</link>
		<comments>http://thinknook.com/10-ways-to-improve-your-classification-algorithm-performance-2013-01-21/#comments</comments>
		<pubDate>Mon, 21 Jan 2013 12:06:35 +0000</pubDate>
		<dc:creator><![CDATA[Links Naji]]></dc:creator>
				<category><![CDATA[Classification]]></category>
		<category><![CDATA[bigrams]]></category>
		<category><![CDATA[classification]]></category>
		<category><![CDATA[corpus]]></category>
		<category><![CDATA[predictiion]]></category>
		<category><![CDATA[stopwords]]></category>
		<category><![CDATA[text classification]]></category>
		<category><![CDATA[unigrams]]></category>

		<guid isPermaLink="false">http://thinknook.com/?p=934</guid>
		<description><![CDATA[In this article I discuss some methods you could adopt to improve the accuracy of your text classifier, I&#8217;ve taken a generalized approach so the recommendations here should really apply for most text classification problem you are dealing with, be it Sentiment Analysis, Topic Classification or any text based classifier. This is by no means [&#8230;]]]></description>
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		<slash:comments>17</slash:comments>
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		<title>Text Classification Threshold Performance Graph</title>
		<link>http://thinknook.com/text-classification-threshold-performance-graph-2013-01-20/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=text-classification-threshold-performance-graph</link>
		<comments>http://thinknook.com/text-classification-threshold-performance-graph-2013-01-20/#comments</comments>
		<pubDate>Sun, 20 Jan 2013 20:08:23 +0000</pubDate>
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				<category><![CDATA[Classification]]></category>

		<guid isPermaLink="false">http://thinknook.com/?p=927</guid>
		<description><![CDATA[One way to increase the accuracy of a classification algorithm is to allow the algorithm to return an &#8220;Unknown&#8221; value, particularly when the probability of what we are trying to classify is too low to simply belong in one class and the algorithm is essentially guessing an answer, leading to incorrect classification. In this post [&#8230;]]]></description>
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		<slash:comments>1</slash:comments>
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		<title>Testing &amp; Diagnosing a Text Classification Algorithm</title>
		<link>http://thinknook.com/testing-diagnosing-a-text-classification-algorithm-2013-01-19/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=testing-diagnosing-a-text-classification-algorithm</link>
		<comments>http://thinknook.com/testing-diagnosing-a-text-classification-algorithm-2013-01-19/#comments</comments>
		<pubDate>Sat, 19 Jan 2013 17:37:26 +0000</pubDate>
		<dc:creator><![CDATA[Links Naji]]></dc:creator>
				<category><![CDATA[Classification]]></category>
		<category><![CDATA[Data-Mining]]></category>
		<category><![CDATA[accuracy]]></category>
		<category><![CDATA[classification]]></category>
		<category><![CDATA[confusion matrix]]></category>
		<category><![CDATA[nltk]]></category>
		<category><![CDATA[precision]]></category>
		<category><![CDATA[recall]]></category>
		<category><![CDATA[text classification]]></category>

		<guid isPermaLink="false">http://thinknook.com/?p=922</guid>
		<description><![CDATA[To get something going with text (or any) classification algorithm is easy enough, all you need is an algorithm, such as Maximum Entropy or Naive Bayes, an implementation of each is available in many different flavors across various programming languages (I use NLTK on Python for text classification), and a bunch of already classified corpus data [&#8230;]]]></description>
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		<slash:comments>2</slash:comments>
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