Description: Algorithm using k-means clustering, K-means algorithm Euclidean distance as a similarity measure, it is the pursuit of the vector V corresponding to a initial cluster centers classification, making the minimum evaluation J. The algorithm uses the error square and guidelines function as the clustering criterion function.
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File list (Check if you may need any files):
kmeans\Debug\kmeans.exe
......\.....\kmeans.ilk
......\.....\kmeans.pdb
......\ipch\kmeans-5252bde7\kmeans-7736984b.ipch
......\kmeans\Debug\CL.read.1.tlog
......\......\.....\CL.write.1.tlog
......\......\.....\kmeans.exe.embed.manifest
......\......\.....\kmeans.exe.embed.manifest.res
......\......\.....\kmeans.exe.intermediate.manifest
......\......\.....\kmeans.lastbuildstate
......\......\.....\kmeans.log
......\......\.....\kmeans.obj
......\......\.....\kmeans_manifest.rc
......\......\.....\link-cvtres.read.1.tlog
......\......\.....\link-cvtres.write.1.tlog
......\......\.....\link.6208-cvtres.read.1.tlog
......\......\.....\link.6208-cvtres.write.1.tlog
......\......\.....\link.6208.read.1.tlog
......\......\.....\link.6208.write.1.tlog
......\......\.....\link.read.1.tlog
......\......\.....\link.write.1.tlog
......\......\.....\mt.read.1.tlog
......\......\.....\mt.write.1.tlog
......\......\.....\rc.read.1.tlog
......\......\.....\rc.write.1.tlog
......\......\.....\vc100.idb
......\......\.....\vc100.pdb
......\......\kmeans.c
......\......\kmeans.vcxproj
......\......\kmeans.vcxproj.filters
......\......\kmeans.vcxproj.user
......\kmeans.sdf
......\kmeans.sln
......\kmeans.suo
......\ipch\kmeans-5252bde7
......\kmeans\Debug
......\Debug
......\ipch
......\kmeans
kmeans
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