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- rm(list=ls())
- library("dbscan")
- dcdata = read.csv('dcdata.txt')
- target = dcdata[,3]
- dcdata = dcdata[,1:2]
- d = dist(dcdata)
- ############ A
- # Perform hierarchical clustering with single link
- hc_single = hclust(d, method = "single")
- clustersSingle = cutree(hc_single, k = 2)
- ########### B
- # Perform hierarchical clustering with complete link
- hc_complete = hclust(d, method = "complete")
- clustersComplete = cutree(hc_complete, k = 2)
- ########### C
- model = dbscan(dcdata, eps = 0.75, minPts = 5)
- clusters1 = model$cluster
- model = dbscan(dcdata, eps = 1, minPts = 5)
- clusters2 = model$cluster
- model = dbscan(dcdata, eps = 1.25, minPts = 5)
- clusters3 = model$cluster
- model = dbscan(dcdata, eps = 1.5, minPts = 5)
- clusters4 = model$cluster
- model = kmeans(dcdata, 2)
- clusterKMeans = model$cluster
- # Q1 - kmeans and complete linkage hierarchical
- plot(dcdata, col = clusters1 + 1, pch = 15, main = "DBSCAN(eps = 0.75, minPts = 5)")
- plot(dcdata, col = clusters2 + 1, pch = 15, main = "DBSCAN(eps = 1, minPts = 5)")
- plot(dcdata, col = clusters3 + 1, pch = 15, main = "DBSCAN(eps = 1.25, minPts = 5)")
- plot(dcdata, col = clusters4 + 1, pch = 15, main = "DBSCAN(eps = 1.5, minPts = 5)")
- plot(dcdata, col = clusterKMeans + 1, pch = 15, main = "kMeans")
- plot(dcdata, col = clustersSingle, pch = 15, main = "Single Linkage")
- plot(dcdata, col = clustersComplete, pch = 15, main = "Complete Linkage")
- # Q2
- Accuracy(clustersSingle, target)
- # Q3
- Accuracy(clustersComplete, target)
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