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?? apriori算法是數據挖掘的經典算法之1,其基于關聯規則的思想.這是我的第2個收藏算法
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appearance to be used with all items not mentioned in the appearancesfile. Other records state the appearance of specific items. The firstfield states the item, the second the appearance indicator. If noappearance indicator is given, the item will be ignored (i.e. mayappear neither in the body (antecedent) nor in the head (consequent)of a rule). Empty records are ignored.</p><p>The following appearance indicators are recognized:</p><ul type=circle><li>item may appear only in rule bodies (antecedents):<br>    <tt>i in b body a ante antecedent</tt></li><li>item may appear only in rule heads (consequents):<br>    <tt>o out h head c cons consequent</tt></li><li>item may appear in rule bodies (antecedents)    or in rule heads (consequents):<br>    <tt>io inout bh b&amp;h ac a&amp;c both</tt></li><li>item may appear neither in rule bodies (antecedents)    nor in rule heads (consequents):<br>    <tt>n neither none ign ignore -</tt></li></ul><p><b>Example 1:</b>Generate only rules with item "x" in the consequent.</p><p><tt>in<br>       x out</tt></p><p><b>Example 2:</b>Item "x" may appear only in a rule head (consequent),item "y" only in a rule body (antecedent);appearance of all other items is not restricted.</p><p><tt>both<br>       x head<br>       y body</tt></p><p>Providing no item appearances file is equivalent to an itemappearances file containing only an indicator like "both", whichdoes not restrict the appearance of any items.</p><table width="100%" border=0 cellpadding=0 cellspacing=0><tr><td width="95%" align=right><a href="#top">back to the top</a></td>    <td width=5></td>    <td><a href="#top"><img src="uparrow.gif" border=0></a></td></tr></table><!-- =============================================================== --><p><img src="line.gif" alt="" height=7 width=704></p><h3><a name="output">Output Format</a></h3><h4><a name="ruleout">Output Format for Association Rules</a></h4><p>Each line of the output file contains one association rule in theformat</p><p><tt>c &lt;- a b ... (x%, y%)</tt></p><p>where a, b, and c are item identifiers, and</p><table border=0 cellpadding=0 cellspacing=0><tr><td valign=top>x</td><td width=10></td>    <td>the percentage of transactions that contain all items appearing    in the rule body (antecedent), that is, in the example above,    a and b. (support of the rule, i.e., the support in my    interpretation)</td><tr><td valign=top>y</td><td></td>    <td>the confidence of the rule, which is computed as the quotient of    the percentage of transactions that contain all items appearing in    the rule body (antecedent) and the rule head (consequent) - that is,    in the example above, a, b, and c - and the above percentage x.</td>    </tr></table><p>If the option -o is used, x is replaced by the rule support in theoriginal definition (i.e., the one used by [Agrawal et al. 1993]),namely the percentage of transactions that contain all items appearingin the rule (antecedent) and the rule head (consequent), that is, inthe example above, a, b, and c. The value of y, however, is stillcomputed from the value of x as described above.</p><p>If the option -x is given, both types of rule support (support ofall items in the rule and support of the items in the body/antecedentof the rule) will be printed. The confidence of a rule (see above) isthe quotient of the two support values (* 100%), i.e., a rule willbe printed as</p><p><tt>c &lt;- a b ... (x<sub>1</sub>%, x<sub>2</sub>%, y%)</tt></p><p>where x<sub>1</sub> is the support of the set of all items in therule, x<sub>2</sub> is the support of the set of items in the body(antecedent) of the rule, and y = x<sub>1</sub>/x<sub>2</sub> * 100%is the confidence of the rule.</p><p>If the option -a is given, the support percentage x is supplementedby the absolute number of transactions underlying it:</p><p><tt>c &lt;- a b ... (x%/s, y%)</tt></p><p>where s is the absolute number of transactions. If the option -x isgiven, the absolute support is printed for both types of rule support.</p><table width="100%" border=0 cellpadding=0 cellspacing=0><tr><td width="95%" align=right><a href="#top">back to the top</a></td>    <td width=5></td>    <td><a href="#top"><img src="uparrow.gif" border=0></a></td></tr></table><!-- =============================================================== --><h4><a name="setout">Output Format for Frequent Item Sets</a></h4><p>Each line of the output file contains one item set in the format</p><p><tt>a b c ... (x%)</tt></p><p>where a, b, and c are item identifiers and x is the percentage oftransactions that contain this item set (item set support).</p><p>If the option -a is given, this percentage is supplemented by theabsolute number of transactions underlying it:</p><p><tt>a b c ... (x%/s)</tt></p><p>where s is the absolute number of transactions.</p><p>If the option -x is given, the percentage of transactions that areidentical to the item set is printed, too (whereas the normal supportis the percentage of transactions that are a superset of the item set):</p><p><tt>a b c ... (x%, %y)</tt></p><p>where x is the normal item set support and y is the percentage oftransactions identical to the item set. (This output option was addedin response to a request by Laura Maruster.) If the option -a is alsogiven, both percentages are supplemented by the absolute number oftransactions underlying these percentages.</p><p>Note that for frequent item sets the option -x cannot be combinedwith the option -y. That is, in order to compute the second supportmeasure for item sets, the transactions have to be loaded into memory.</p><table width="100%" border=0 cellpadding=0 cellspacing=0><tr><td width="95%" align=right><a href="#top">back to the top</a></td>    <td width=5></td>    <td><a href="#top"><img src="uparrow.gif" border=0></a></td></tr></table><!-- =============================================================== --><h4><a name="edgeout">Output Format for Association Hyperedges</a></h4><p>Each line of the output file contains one hyperedge the format</p><p><tt>a b c ... (x%, y%)</tt></p><p>where a, b, and c are item identifiers, and</p><table border=0 cellpadding=0 cellspacing=0><tr><td valign=top>x</td><td width=10></td>    <td>the percentage of transactions that contain all items appearing    in the hyperedge, that is, in the example above, a, b, and c.</td>    </tr><tr><td valign=top>y</td><td></td>    <td>the average confidence of all rules that can be formed using    the items in the hyperedge with all items appearing in the rule    (see above), i.e., for the example above, the average confidence    of the rules c &lt;- a b, b &lt;- a c, and a &lt;- b c.</td></tr></table><p>If the option -a is given, the support percentage x is supplementedby the absolute number of transactions underlying it:</p><p><tt>a b c ... (x%/s, y%)</tt></p><p>where s is the absolute number of transactions.</p><table width="100%" border=0 cellpadding=0 cellspacing=0><tr><td width="95%" align=right><a href="#top">back to the top</a></td>    <td width=5></td>    <td><a href="#top"><img src="uparrow.gif" border=0></a></td></tr></table><!-- =============================================================== --><p><img src="line.gif" alt="" height=7 width=704></p><h3><a name="copying">Copying</a></h3><p>apriori -   find association rules/hyperedges with apriori algorithm<br>   copyright &copy; 1996-2002  Christian Borgelt</p><p>This program is free software; you can redistribute it and/ormodify it under the terms of the<a href="http://www.fsf.org/copyleft/lesser.html">GNU Lesser (Library) General Public License</a> as published by the<a href="http://www.fsf.org">Free Software Foundation</a>.</p><p>This program is distributed in the hope that it will be useful,but WITHOUT ANY WARRANTY; without even the implied warranty ofMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the<a href="http://www.fsf.org/copyleft/lesser.html">GNU Lesser (Library) General Public License</a> for more details.</p><table width="100%" border=0 cellpadding=0 cellspacing=0><tr><td width="95%" align=right><a href="#top">back to the top</a></td>    <td width=5></td>    <td><a href="#top"><img src="uparrow.gif" border=0></a></td></tr></table><!-- =============================================================== --><p><img src="line.gif" alt="" height=7 width=704></p><h3><a name="download">Download</a></h3><table border=0 cellpadding=0 cellspacing=0><tr><td valign=top><b>Sources:</b></td><td></td>    <td><a href="http://fuzzy.cs.uni-magdeburg.de/~borgelt/src/apriori.tar.gz">    apriori.tar.gz</a> (83 kb)    <a href="http://fuzzy.cs.uni-magdeburg.de/~borgelt/src/apriori.zip">    apriori.zip</a> (94 kb)    (version 4.0, 12.02.2002)</td></tr><tr><td valign=top><b>Unix:</b></td><td    width=10></td>    <td><a href="http://fuzzy.cs.uni-magdeburg.de/~borgelt/src/apriori">    apriori</a> (Linux executable, 49 kb)</td></tr><tr><td valign=top><b>Windows:</b></td><td></td>    <td><a href="http://fuzzy.cs.uni-magdeburg.de/~borgelt/src/apriori.exe">    apriori.exe</a> (Windows console executable, 88 kb)</td></tr></table><table width="100%" border=0 cellpadding=0 cellspacing=0><tr><td width="95%" align=right><a href="#top">back to the top</a></td>    <td width=5></td>    <td><a href="#top"><img src="uparrow.gif" border=0></a></td></tr></table><!-- =============================================================== --><p><img src="line.gif" alt="" height=7 width=704></p><h3><a name="contact">Contact</a></h3><table border=0 cellpadding=0 cellspacing=0><tr><td valign=top>Snail mail:</td><td width=10></td>    <td><a href="http://fuzzy.cs.uni-magdeburg.de/~borgelt/index.html">        Christian Borgelt</a><br>        <a href="http://fuzzy.cs.uni-magdeburg.de/index.html">        Working Group Neural Networks and Fuzzy Systems</a><br>        <a href="http://www-iws.cs.uni-magdeburg.de/iws.html">         Department of Knowledge Processing and Language Engineering</a><br>        <a href="http://www.cs.uni-magdeburg.de/">        School of Computer Science</a><br>        <a href="http://www.uni-magdeburg.de/">        Otto-von-Guericke-University of Magdeburg</a><br>        Universit&auml;tsplatz 2<br>        D-39106 Magdeburg<br>        Germany</td></tr><tr><td valign=top>E-mail:</td><td></td>    <td><a href="mailto:christian.borgelt@cs.uni-magdeburg.de">        christian.borgelt@cs.uni-magdeburg.de</a><br>        <a href="mailto:borgelt@iws.cs.uni-magdeburg.de">        borgelt@iws.cs.uni-magdeburg.de</a></td></tr><tr><td>Phone:</td><td></td>    <td>+49 391 67 12700</td></tr><tr><td>Fax:</td><td></td>    <td>+49 391 67 12018</td></tr><tr><td>Office:</td><td></td>    <td>03.206</td></tr></table><table width="100%" border=0 cellpadding=0 cellspacing=0><tr><td width="95%" align=right><a href="#top">back to the top</a></td>    <td width=5></td>    <td><a href="#top"><img src="uparrow.gif" border=0></a></td></tr></table><!-- =============================================================== --><p><img src="line.gif" alt="" height=7 width=704></p><address>&copy; 2002<a href="mailto:borgelt@iws.cs.uni-magdeburg.de">Christian Borgelt</a></address><!-- Created: Thu May 24 12:28:05 CEST 2001 --><!-- hhmts start -->Last modified: Tue Feb 12 22:54:10 CET 2002<!-- hhmts end --></body></html>

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