文件名称:julei
- 所属分类：
- 并行运算
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2012-11-26
- 文件大小：
- 8.7mb
- 下载次数：
- 0次
- 提 供 者：
- S5145*****
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
遗传算法解决聚类问题。.边的权重与时间关系为：1-（用户最近标注时间-该边被标注时间)*0.01,时间间隔以月计，相差一个月权重相差0.01,最近标注的权重为1
2.边的权重通过端点的出度调整
3.若用户没有共现标签，则以其权重最大的部分标签自连接构造标签对
4.若用户标签对少于预设大小，则将其拥有的标签对重复多次，直到数量与预设大小相等-Clustering genetic algorithm to solve the problem. . While the weight and time are: 1- (user recently marked the time- the edge is marked time)* 0.01, the time interval in months, a difference of a month the weight difference of 0.01, recently marked the weight is 1 2 edge weight degree of adjustment by the end of the 3 co-occurrence, if the user does not label, then the weight of the largest part of its label from the label of the connecting structure (4) If the user label for less than the default size, it is repeated several times with the labels until equal to the number and the default size
2.边的权重通过端点的出度调整
3.若用户没有共现标签，则以其权重最大的部分标签自连接构造标签对
4.若用户标签对少于预设大小，则将其拥有的标签对重复多次，直到数量与预设大小相等-Clustering genetic algorithm to solve the problem. . While the weight and time are: 1- (user recently marked the time- the edge is marked time)* 0.01, the time interval in months, a difference of a month the weight difference of 0.01, recently marked the weight is 1 2 edge weight degree of adjustment by the end of the 3 co-occurrence, if the user does not label, then the weight of the largest part of its label from the label of the connecting structure (4) If the user label for less than the default size, it is repeated several times with the labels until equal to the number and the default size
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下载文件列表
聚类推荐（传引用）\breast-cancer-wisconsin.data
..................\clusteringEvaluation.m
..................\disInnerClusterComputing.asv
..................\disInnerClusterComputing.m
..................\distanceComputing.m
..................\distanceComputing2.m
..................\dis_yeast.txt
..................\eig.prj
..................\findNameInClass.asv
..................\findNameInClass.m
..................\fMeasure.asv
..................\fMeasure.m
..................\fMeasureComputing.asv
..................\fMeasureComputing.m
..................\getClusters.m
..................\getKEigenVector.m
..................\HMDistanceComputing.m
..................\incrementalSearchClustering.asv
..................\incrementalSearchClustering.m
..................\initialKmeansClustering.asv
..................\initialKmeansClustering.m
..................\initialKmeansClustering2.m
..................\initialKmeansClustering3.m
..................\initialKmeansClustering4.m
..................\iris.data
..................\kmeansClustering.m
..................\makeInitCluster.asv
..................\makeInitCluster.m
..................\makeNewByReplaceOnlyOne.m
..................\makeNewCenter.m
..................\makeNewCenter2.m
..................\makeNewClusters.m
..................\makeRepalcePairs.m
..................\movement_libras.data
..................\nMedoidsClustering.m
..................\printDis.m
..................\printDis2File.m
..................\readBreastCancer.asv
..................\readBreastCancer.m
..................\readIris.m
..................\readIrise.asv
..................\readMovementInitialData.asv
..................\readMovementInitialData.m
..................\readSoybean.m
..................\readspanbase.m
..................\readTransfusion.asv
..................\readTransfusion.m
..................\readWDBCInitialData.asv
..................\readWDBCInitialData.m
..................\readyeast.asv
..................\readyeast.m
..................\readZoo.m
..................\reaWine.asv
..................\reaWine.m
..................\reaZoo.asv
..................\replaceProfitComputing.asv
..................\replaceProfitComputing.m
..................\r_train.txt
..................\spambase.data
..................\topusers1.txt
..................\topusers2.txt
..................\trainingset.txt
..................\transfusion.data
..................\t_train.txt
..................\Untitled2.m
..................\Untitledx.asv
..................\Untitledx.m
..................\u_count.txt
..................\u_train.txt
..................\wdbc.data
..................\wine.data
..................\yeast.data
..................\zoo.data
..................\算法实现要点.txt
聚类推荐（传引用）
..................\clusteringEvaluation.m
..................\disInnerClusterComputing.asv
..................\disInnerClusterComputing.m
..................\distanceComputing.m
..................\distanceComputing2.m
..................\dis_yeast.txt
..................\eig.prj
..................\findNameInClass.asv
..................\findNameInClass.m
..................\fMeasure.asv
..................\fMeasure.m
..................\fMeasureComputing.asv
..................\fMeasureComputing.m
..................\getClusters.m
..................\getKEigenVector.m
..................\HMDistanceComputing.m
..................\incrementalSearchClustering.asv
..................\incrementalSearchClustering.m
..................\initialKmeansClustering.asv
..................\initialKmeansClustering.m
..................\initialKmeansClustering2.m
..................\initialKmeansClustering3.m
..................\initialKmeansClustering4.m
..................\iris.data
..................\kmeansClustering.m
..................\makeInitCluster.asv
..................\makeInitCluster.m
..................\makeNewByReplaceOnlyOne.m
..................\makeNewCenter.m
..................\makeNewCenter2.m
..................\makeNewClusters.m
..................\makeRepalcePairs.m
..................\movement_libras.data
..................\nMedoidsClustering.m
..................\printDis.m
..................\printDis2File.m
..................\readBreastCancer.asv
..................\readBreastCancer.m
..................\readIris.m
..................\readIrise.asv
..................\readMovementInitialData.asv
..................\readMovementInitialData.m
..................\readSoybean.m
..................\readspanbase.m
..................\readTransfusion.asv
..................\readTransfusion.m
..................\readWDBCInitialData.asv
..................\readWDBCInitialData.m
..................\readyeast.asv
..................\readyeast.m
..................\readZoo.m
..................\reaWine.asv
..................\reaWine.m
..................\reaZoo.asv
..................\replaceProfitComputing.asv
..................\replaceProfitComputing.m
..................\r_train.txt
..................\spambase.data
..................\topusers1.txt
..................\topusers2.txt
..................\trainingset.txt
..................\transfusion.data
..................\t_train.txt
..................\Untitled2.m
..................\Untitledx.asv
..................\Untitledx.m
..................\u_count.txt
..................\u_train.txt
..................\wdbc.data
..................\wine.data
..................\yeast.data
..................\zoo.data
..................\算法实现要点.txt
聚类推荐（传引用）