Formation of higher dimensional subspace clusters

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Silpa K 2020-1-27

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https://ww2.mathworks.cn/matlabcentral/answers/502188-formation-of-higher-dimensional-subspace-clusters

评论： Hiro Yoshino 2020-1-30

采纳的回答： Hiro Yoshino

Glassxl.xlsx

在 MATLAB Online 中打开

How to find higher dimensional clusters are formed by connecting 2-dimensional subspace clusters sharing common objects. If an outlier object is by chance becomes part of a one dimensional cluster, it will be absent in clusters present in remaining dimensions and its support will be below attribute_threshold. Such outlier objects get eliminated in this step. The attributes containing 2-dimensional clusters are arranged in non-decreasing order on the basis of percentage of coverage of the data items belonging to the clusters. The objects in a 2-dimensional cluster in an attribute are connected to objects in next attribute in the sequence if they contain common object indices to form higher dimensional subspace clusters. And find the count of dimensions in a subspace cluster is less than attribute_threshold.The default attribute threshold is set as 5.I want to do that in Z.

clc;
clear;
data=xlsread('Glassxl.xlsx');
asc=sort(data);
 minpts=4;
  epsilon=2;
tic
idx=dbscan(asc,epsilon,minpts);
figure(1)
gscatter(asc(:,1),asc(:,2),idx);
title('DBSCAN Using Euclidean Distance Metric')
Z = linkage(idx,'ward');