<?xml version="1.0"?>
<items>

	
	<item> 
		<title>
		    Fast Effective Rule Induction
		</title>
	        <apropos id="189" author="stuff" dob="1189908642" />
       		<link>http://citeseer.nj.nec.com/cohen95fast.html</link>
       		<category>misc</category>
		<description>
			<![CDATA[<dl>
				<dt>who</dt><dd>
					William W. Cohen
				</dd>
				<dt>when</dt><dd>
					1995
				</dd>
				<dt>where</dt><dd>
					Proc. of the 12th International Conference on Machine Learning,
					    pages 115--123
				</dd>
			</dl>]]>
		</description>
	</item>


  <item>
    <title>Statistical Comparisons of Classifiers over Multiple
    Data Sets</title>
    <apropos id="151" author="timm" dob="1187456729" />
    <link>http://menzies.us/cs591o/pdf/demsar06a.pdf</link>
	<category>journal</category>
    <description><![CDATA[<dl>
    <dt>who</dt><dd>Janes Demsar</dd>
    <dt>when</dt><dd>2006</dd>
    <dt>where</dt><dd>Journal of Machine Learning Reseaerch, 7, p1-30</dd>
	</dl>]]></description>
  </item>

	
	<item> 
		<title>
			On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
		</title>
	        <apropos id="187" author="stuff" dob="1189902459" />
       		<link>http://citeseer.ist.psu.edu/domingos97optimality.html</link>
       		<category>journal</category>
		<description><![CDATA[<dl>
		<dt>who</dt><dd>
			Pedro Domingos and Michael J. Pazzani</dd>
		<dt>when</dt><dd>
			1997</dd>
		<dt>where</dt><dd>
			Machine Learning, vol 29, number 2-3, pages 103-130		
		</dd>
		</dl>]]></description>
	</item>


  <item>
    <title>Supervised and Unsupervised Discretization of Continuous
    Feature</title>
    <apropos id="135" author="timm" dob="1187220997" />
    <link>
    http://menzies.us/cs591o/pdf/dougherty95supervised.pdf</link>
    <category>paper</category>
    <category>conference</category>
    <description><![CDATA[<dl>
    <dt>who</dt><dd>J. Dougherty and R. Kohavi and M. Sahami,</dd>
    <dt>when</dt><dd>1995</dd>
    <dt>where</dt><dd>International Conference on Machine Learning,
    p194-202</dd>
	</dl>]]></description>
  </item>

  <item>
    <title>Separate-and-conquer rule learning</title>
    <apropos id="153" author="timm" dob="1187457556" />
    <link>
    http://menzies.us/cs5910/pdf/separate-and-conquer-rule.pdf</link>
    <category>journal</category>
    <description><![CDATA[<dl>
    <dt>who</dt><dd>J. Furnkranz</dd>
    <dt>when</dt><dd>1999</dd>
    <dt>where</dt><dd>Artificial Intelligence Review, 13, pages 3--54.</dd>
	</dl>]]></description>
  </item>

	
	<item> 
		<title>
		    Benchmarking Attribute Selection Techniques for Discrete Class Data Mining
		</title>
	        <apropos id="192" author="stuff" dob="1189910694" />
       		<link>http://citeseer.ist.psu.edu/hall03benchmarking.html</link>
       		<category>misc</category>
		<description>
			<![CDATA[<dl>
				<dt>who</dt><dd>
					 Mark A. Hall, Geoffrey Holmes
				</dd>
				<dt>when</dt><dd>
					2003
				</dd>
				<dt>where</dt><dd>
					IEEE TKDE 2003
				</dd>
			</dl>]]>
		</description>
	</item>


  <item>
    <title>Very Simple Classification Rules Perform Well on Most
    Commonly Used Datasets</title>
    <apropos id="136" author="timm" dob="1187221185" />
    <link>http://menzies.us/cs591o/pdf/93holte.pdf</link>
    <category>paper</category>
    <category>journal</category>
    <description><![CDATA[<dl>
    <dt>who</dt><dd>Robert C. Holte</dd>
    <dt>when</dt><dd>1993</dd>
    <dt>where</dt><dd>Machine Learning, 11, p63.</dd>
	</dl>]]></description>
  </item>
  <item>
    <title>On a test of Whether One of Two Random Variables Is
    Stochastically Larger than the Other</title>
    <apropos id="152" author="timm" dob="1187457010" />
    <link>http://menzies.us/cs591o/pdf/mannWhitney47.pdf</link>
    <category>journal</category>
    <description><![CDATA[<dl>
    <dt>who</dt><dd>H.B. Mann and D.R. Whitney</dd>
    <dt>when</dt><dd>1947</dd>
    <dt>where</dt><dd>The Annals of Mathematical Statistics, p50-60</dd>
	</dl>]]></description>
  </item>

	
	<item> 
		<title>
		    Explanation vs Performance in Data Mining: 
			A Case Study with Predicting Runaway Projects
		</title>
	        <apropos id="191" author="stuff" dob="1189909531" />
       		<link>http://unbox.org/wisp/var/timm/var/kddse-v5twoColumn.pdf</link>
       		<category>misc</category>
		<description>
			<![CDATA[<dl>
				<dt>who</dt><dd>
					Tim Menzies, Osamu Mizuno, Yasunari Takagi and Tohru Kikuno 
				</dd>
				<dt>when</dt><dd>
					2007
				</dd>
				<dt>where</dt><dd>
					Draft paper, submitted to IEEE TSE 2007
				</dd>
			</dl>]]>
		</description>
	</item>

	<item>
		<title>
			Explanation vs Performance in Data Mining: 
			A Case Study with Predicting Runaway Projects
		</title>
	        <apropos id="190" author="stuff" dob="1189909372" />
       		<link>http://menzies.us/cs591o/?doc=190</link>
       		<category>draft</category>
		<description>
			<![CDATA[
				DESCRIPTION
			]]>
		</description>
	</item>



  <item>
    <title>Data Mining, 2nd edition</title>
    <apropos id="122" author="timm" dob="1187215598" />
    <link>
    http://www.amazon.com/exec/obidos/ASIN/0120884070/departmofcompute/002-4075571-4679224/</link>
    <category>book</category>
    <description><![CDATA[<dl>
    <dt>who</dt><dd>Ian Witten and Elbe Frank</dd>
    <dt>when</dt><dd>2005</dd>
    <dt>where</dt><dd>Addison Wesley</dd>
	</dl>]]></description>
  </item>
	
	<item> 
		<title>
		    Proportional k-Interval Discretization for Naive-Bayes Classifiers
		</title>
	        <apropos id="188" author="stuff" dob="1189903532" />
       		<link>http://www.csse.monash.edu/~webb/Files/YangWebb03.pdf</link>
       		<category>conference</category>
		<description>
			<![CDATA[<dl>
				<dt>who</dt><dd>
					Y. Yang and G. Webb
				</dd>
				<dt>when</dt><dd>
					2003
				</dd>
				<dt>where</dt><dd>
					Proceedings of the 7th Pacific-Asia Conference on 
					Knowledge Discovery and Data Mining (PAKDD 2003)
				</dd>
			</dl>]]>
		</description>
	</item>

</items>
