[R] Need help with use of ROCK algorithm in R for binary data
Matej Zuzčák
mzuzcak at secit.sk
Mon Aug 15 11:22:32 CEST 2016
Dear list members,
I have one appeal for you.
I need use ROCK (RockCluster) algorithm for binary data in R. My binary
data looks this:
objects cat1 cat2 cat3 cat4 ...A TRUE FALSE FALSE FALSE B TRUE FALSE
TRUE FALSE C TRUE FALSE FALSE FALSE D FALSE TRUE TRUE TRUE E TRUE TRUE
TRUE TRUE F TRUE FALSE TRUE FALSE
Now I need clasify these objects AF to clusters. I apply this procedure
https://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Clustering/RockCluster#Dataset
But I have several problems.
1. I import data from CSV file. db < read.csv(file="file.csv",
header=TRUE, sep="") Fields are 1 (TRUE) and 0 (FALSE).
2. I convert this data: x < as.dummy(db[1]). After this step all
columns in x are duplicated with 1 and 0. Why? It is correct please?
3. rc < rockCluster(x, n=4, debug=TRUE)
4. rf < fitted(rc) Why fitted and when rather use predict(rc, x)?
5. table(db$objects, rf$cl) After I get this output:
 1 NA
A 1 0
B 1 0
C 1 0
D 0 1
E 0 1
F 0 1

What way I can read this output? What objects are in clusters with
other? What objects are the most similar please?
Many thanks for your help.

Best Regards
Matej Zuzcak
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