数据挖掘论文 where p Cluster Equals(cluster) select //遍历这一簇所有数据 foreach (var cluserRow in clusterStaff) //计算距离 double orgTempAge Math Pow(orgAge-cluserRow Age Value, 2) double orgTempHeight Math Pow(orgHeight cluserRow. Height. Value, 2) double orgTempWeight Math Pow(orgWeight cluserRow. Weight Value, 2) double orgDistance Math Sgrt(orgTempAge orgTempHeight+ orgTempWeight) double randomTempAge = Math. Pow(randomAge-cluserRow Age Value, 2) double random TempHeight Math Pow (randomHeight cluserRow. Height Value, 2) double randomTempWeight Math Pow(randoml cluserRow. Weight. Value, 2) double randomDistance Math Sart (randomTempAge randomTempHeight randomTempWeight) orgCount + orgDistance random Count + randomDistance //得到交换后它们的代价 sub randomCount -orgCount return sub ///< ///k中心点算法 ///< //< param name="k">分成k簇</ paran> ///< param name=" Orgionliststaff">原数据</ param> /// <returns></returns> public List<Staff> K method (int k, List<Staff>OrgionListStaff) //初始化总代价 //判断是否所有的中心点不在变化标志 bool Changed = true /初始化一个随机数生成器 andom ccy new Random o //得到所有数据的个数 int count OrgionListstaff Count //初始化整个数据变化后保存的链表集合数据挖掘论文 15 where p.Cluster.Equals(cluster) select p; //遍历这一簇所有数据 foreach (var cluserRow in clusterStaff) { //计算距离 double orgTempAge = Math.Pow(orgAge - cluserRow.Age.Value, 2); double orgTempHeight = Math.Pow(orgHeight - cluserRow.Height.Value, 2); double orgTempWeight = Math.Pow(orgWeight - cluserRow.Weight.Value, 2); double orgDistance = Math.Sqrt(orgTempAge + orgTempHeight + orgTempWeight); double randomTempAge = Math.Pow(randomAge - cluserRow.Age.Value, 2); double randomTempHeight = Math.Pow(randomHeight - cluserRow.Height.Value, 2); double randomTempWeight = Math.Pow(randomWeight - cluserRow.Weight.Value, 2); double randomDistance = Math.Sqrt(randomTempAge + randomTempHeight + randomTempWeight); orgCount += orgDistance; randomCount += randomDistance; } //得到交换后它们的代价 sub = randomCount - orgCount; return sub; } /// <summary> /// k中心点算法 /// </summary> /// <param name="k">分成k簇</param> /// <param name="OrgionListStaff">原数据</param> /// <returns></returns> public List<Staff> K_method(int k, List<Staff> OrgionListStaff) { //初始化总代价 double s = 0; //判断是否所有的中心点不在变化标志 bool Changed = true; //初始化一个随机数生成器 Random ccy = new Random(); //得到所有数据的个数 int count = OrgionListStaff.Count; //初始化整个数据变化后保存的链表集合