Consider the TopUniversities dataset used in class, which has 25 records. The dendrogram below is generated by the singl

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answerhappygod
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Consider the TopUniversities dataset used in class, which has 25 records. The dendrogram below is generated by the singl

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Consider the TopUniversities datasetused in class, which has 25 records. The dendrogram below isgenerated by the single linkage algorithm in Weka based on thedataset. The subsequent two screens show the k-meansclustering results using Weka, where k = 4 andthe clusters are labeled from cluster 0 to cluster 3. Answerquestions (a), (b) and (c) following the screens.
Consider The Topuniversities Dataset Used In Class Which Has 25 Records The Dendrogram Below Is Generated By The Singl 1
Consider The Topuniversities Dataset Used In Class Which Has 25 Records The Dendrogram Below Is Generated By The Singl 1 (22.82 KiB) Viewed 10 times
Consider The Topuniversities Dataset Used In Class Which Has 25 Records The Dendrogram Below Is Generated By The Singl 2
Consider The Topuniversities Dataset Used In Class Which Has 25 Records The Dendrogram Below Is Generated By The Singl 2 (97.44 KiB) Viewed 10 times
Consider The Topuniversities Dataset Used In Class Which Has 25 Records The Dendrogram Below Is Generated By The Singl 3
Consider The Topuniversities Dataset Used In Class Which Has 25 Records The Dendrogram Below Is Generated By The Singl 3 (61.18 KiB) Viewed 10 times
Weka Classifier Tree Visualizer: 16:39:46 HierarchicalClusterer (T... ..... O x 07.06.05.03.05.05.01.04.00.09.00.02.08.04.02.07.05.07.08.01.00.09.01.07.02.

Weka Explorer Preprocess Classify Cluster Associate Select attributes Visualize Clusterer Choose SimpleKMeans -N 4 -A "weka.core.EuclideanDistance -R first-last" -I 500-S 10 Cluster mode ⒸUse training set Supplied test set Percentage split Classes to clusters evaluation (Num) GradRate Store clusters for visualization Ignore attributes Start Result list (right-click for options) 21:42:08 - SimplekMeans Status OK Set... % 66 Stop Clusterer output kMeans ====== Number of iterations: 3 Within cluster sum of squared errors: 2.544233125332993 Missing values globally replaced with mean/mode Cluster centroids: Attribute AvgSAT PctTop10Student PctAccept StuFacRatio Expenses GradRate Clustered Instances OHN M 0 1 2 3 === Model and evaluation on training set === 3 ( 12 %) (40 %) Full Data (25) 10 12.6644 76.48 39.2 12.72 27.388 86.72 Time taken to build model (full training data): 0.01 seconds 5 ( 20 %) 7 ( 28 %) Cluster# 0 111 (3) 12.85 70.6667 51 9.6667 40.699 82 1 (10) 12.735 83 33.4 12.8 22.7005 90.2 2 (5) 10.852 44 69.6 18.6 11.0564 74.4 Log 0 3 (7) 13.7786 92.8571 20.7143 9.7143 40.0451 92.5714 x 111 X0

X: University (Nom) Colour: Cluster (Nom) w To ct CCTO Weka Clusterer Visualize: 21:42:08 - SimpleKMeans (TopUniversities) u Plot:TopUniversities_clustered NHOUSTO -110 00 STO Reset OH30DOHO Clear X Open X Save X X Y: Cluster (Nom) Select Instance X x Jitter X X 30 X cluster0 cluster1 cluster2 cluster3 X Harv Yali MIT CalT Brow UChi Corn Colu UVi Carn UCBe Penn Texa Prin Stan Duk Dart John UPen Nort Notr Geor UMic Uwis Purd Class colour X X
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