文件名称:FP-growth-algorithm-implementation
- 所属分类：
- JSP源码/Java
- 资源属性：
- [Java] [源码]
- 上传时间：
- 2012-11-26
- 文件大小：
- 528kb
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- 0次
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- fr***
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FP增长算法的实现与测试(Java实现)
1、程序编译运行环境Eclipse3.20+JDK1.60
2、程序参数说明
-F=filename
-S=support
-C=confidence
filename:数据集文件名，必须位于工程根目录下
support:支持度，位于0-100.0之间的任意数
confidence:置信度，位于0-100.0之间的任意数
例如：-F=anonymous-msweb.data -S=10.0 -C=45.0（参数顺序无关）
3. 程序正确性验证
工程中包含sample.txt文件用来验证。
具体方法：
（1）在AssociationRuleMining 类中，preprocessDataSet函数的最后一条语句替换为fileName = "sample.txt"
（2）在FPgrowth类中，main函数中的 myFPtree.outputARs2() 替换为 myFPtree.outputARs()
（3）输入正确格式的参数，数据集文件名可任意-FP growth algorithm implementation and testing (Java implementation)
1, compiled runtime environment Eclipse3.20+ JDK1.60
2, program parameters that
-F = filename
-S = support
-C = confidence
filename: data set file name, must be located project root directory
support: support, in any number between 0-100.0
confidence: confidence, any number in between 0-100.0
example:-F = anonymous-msweb.data-S = 10.0-C = 45.0 (parameter order has nothing to do)
3. program correctness verification project file contains sample.txt to verify. Specific methods:
(1) AssociationRuleMining class, preprocessDataSet last statement function is replaced fileName = " sample.txt"
(2) in the FPgrowth class, main function in the myFPtree.outputARs2 () replace myFPtree.outputARs ()
(3) Enter the correct format, parameters, file names can be arbitrary data set
1、程序编译运行环境Eclipse3.20+JDK1.60
2、程序参数说明
-F=filename
-S=support
-C=confidence
filename:数据集文件名，必须位于工程根目录下
support:支持度，位于0-100.0之间的任意数
confidence:置信度，位于0-100.0之间的任意数
例如：-F=anonymous-msweb.data -S=10.0 -C=45.0（参数顺序无关）
3. 程序正确性验证
工程中包含sample.txt文件用来验证。
具体方法：
（1）在AssociationRuleMining 类中，preprocessDataSet函数的最后一条语句替换为fileName = "sample.txt"
（2）在FPgrowth类中，main函数中的 myFPtree.outputARs2() 替换为 myFPtree.outputARs()
（3）输入正确格式的参数，数据集文件名可任意-FP growth algorithm implementation and testing (Java implementation)
1, compiled runtime environment Eclipse3.20+ JDK1.60
2, program parameters that
-F = filename
-S = support
-C = confidence
filename: data set file name, must be located project root directory
support: support, in any number between 0-100.0
confidence: confidence, any number in between 0-100.0
example:-F = anonymous-msweb.data-S = 10.0-C = 45.0 (parameter order has nothing to do)
3. program correctness verification project file contains sample.txt to verify. Specific methods:
(1) AssociationRuleMining class, preprocessDataSet last statement function is replaced fileName = " sample.txt"
(2) in the FPgrowth class, main function in the myFPtree.outputARs2 () replace myFPtree.outputARs ()
(3) Enter the correct format, parameters, file names can be arbitrary data set
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下载文件列表
FP增长算法的实现与测试\Program\dbmining\.classpath
......................\.......\........\.project
......................\.......\........\anonymous-msweb.data
......................\.......\........\fpgrowth\AssociationRuleMining$Attr.class
......................\.......\........\........\AssociationRuleMining$RuleNode.class
......................\.......\........\........\AssociationRuleMining.class
......................\.......\........\........\AssociationRuleMining.java
......................\.......\........\........\DataTree.class
......................\.......\........\........\DataTree.java
......................\.......\........\........\FPgrowth.class
......................\.......\........\........\FPgrowth.java
......................\.......\........\........\FPtree$FPgrowthColumnCounts.class
......................\.......\........\........\FPtree$FPgrowthHeaderTable.class
......................\.......\........\........\FPtree$FPgrowthItemPrefixSubtreeNode.class
......................\.......\........\........\FPtree$FPgrowthSupportedSets.class
......................\.......\........\........\FPtree$FPtreeNode.class
......................\.......\........\........\FPtree.class
......................\.......\........\........\FPtree.java
......................\.......\........\........\TreeNode.class
......................\.......\........\........\TreeNode.java
......................\.......\........\my.data
......................\.......\........\sample.txt
......................\.......\FP增长算法的实现与测试.doc
......................\.......\Read me First.txt
......................\.......\dbmining\fpgrowth
......................\.......\dbmining
......................\Program
FP增长算法的实现与测试
......................\.......\........\.project
......................\.......\........\anonymous-msweb.data
......................\.......\........\fpgrowth\AssociationRuleMining$Attr.class
......................\.......\........\........\AssociationRuleMining$RuleNode.class
......................\.......\........\........\AssociationRuleMining.class
......................\.......\........\........\AssociationRuleMining.java
......................\.......\........\........\DataTree.class
......................\.......\........\........\DataTree.java
......................\.......\........\........\FPgrowth.class
......................\.......\........\........\FPgrowth.java
......................\.......\........\........\FPtree$FPgrowthColumnCounts.class
......................\.......\........\........\FPtree$FPgrowthHeaderTable.class
......................\.......\........\........\FPtree$FPgrowthItemPrefixSubtreeNode.class
......................\.......\........\........\FPtree$FPgrowthSupportedSets.class
......................\.......\........\........\FPtree$FPtreeNode.class
......................\.......\........\........\FPtree.class
......................\.......\........\........\FPtree.java
......................\.......\........\........\TreeNode.class
......................\.......\........\........\TreeNode.java
......................\.......\........\my.data
......................\.......\........\sample.txt
......................\.......\FP增长算法的实现与测试.doc
......................\.......\Read me First.txt
......................\.......\dbmining\fpgrowth
......................\.......\dbmining
......................\Program
FP增长算法的实现与测试