数据挖掘WEKA实验报告

1、数据挖掘-WEKA实验报告三姓名及学号：杨珍20131198班级：卓越计科1301指导老师：吴珏老师一、实验内容1、聚类算法（掌握 weka中k-means算法的使用）1）加载 weather.arrf 文件，选择 SimplerKmeans 算法，使用默认参数，进 行聚类。对聚类结果进行分析。2）使用EM算法进行聚类。3）分别使用DBSCA和OPTICS算法进行聚类，对结果进行分析。二、 实验步骤.Niantwr of1Within cluatr 二卫 cf acruazcd cmss; 2.1435SB23157S7Iritiisl ja-ioq pgint (randan);Cluste

2、r 0; S +12.9#.47P1.4. Iris-vEicclQrCluster 1: 6 + 2f 29P 4.3 1,3. IrLB-VBEBXcolozMissing val-e globally rsplayed with aeaa/nodeFial cluer entroids:C： n-inrifrAttributeFull Data(10101103)1 (50)SFpa leiigTh5,B33C.362s, DQgnu砂时ath3,542+5723-4L3pet al length3.75274.906L.454pctalvidth1*13371.6760.244clas

3、sri3-3C333IzinF33.C 313FIr-3-36353(2)使用EM算法进行聚类A Weka Clusterer Visualize: 04:47:02 - EM (inl IiLS ucenumber 皿ui；iI T; it;BlLtaftki Jim)L aGL cur Lius t ar (.Hanii JE. alsct Zus t -one aBesstClearOpenSavePlot：C1S5 cq1?utEHKUjBber of c1jalce selftcte-3 by cicbs 丁甘 1二ioc: 4 ffjnfevf of . *l*eaL1cIia24

4、2iaieAit r Laic*D【叽血12(0.2)3|0+14|ollenixt.WflC；5.H7CMe.tcatd cfen-.d*3 HC：BI IIJ 5.4i 4.4)sil.E+1. Tx4申-msp? SaOiid Iria-seceiSH】iM崭ZCL薪亡r l齐乩并1.5PC.3P:rU fc.a*hIri j-mrtEMeLj a吐l二上:EUrltQ4*Ztir-BetnMZeIjZiL -aL2!.使用OPTICS进行聚类Q weka.gui.GerwricOSectEditorka clusitrtrs. OPTICSBasic implementation of

5、 OPTICS clustering algorithm that should Fo广 be used as a reference for runtime benchmarks: more sophisticated implementations exist! Clustering of new instances is not supported.databas eOutput debug distanceFuncti on doHotCheckC apabili ti es epsilon minFoints showGUI wri teOPIICSresultsMor*Capabiliti esFalseC1TQ亠Open.Save.UK.I ancel二、思考与分析1请