[R] Need help with use of ROCK algorithm in R for binary data

[PIKAL Petr]

Hi

see in line

> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Matej
> Zuzčák
> Sent: Monday, August 15, 2016 11:23 AM
> To: r-help at r-project.org
> Subject: [R] Need help with use of ROCK algorithm in R for binary data
>
> 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|

Better to show your data with dput command. Just copy the output of

dput(header(db, 20))

to your mail.
>
> Now I need clasify these objects A-F to clusters. I apply this procedure
> https://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Clustering/Ro
> ckCluster#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).

Hm. Why do you use csv if you set the separator to "|". I would use read.table.

>  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?

Hm. Strange. In help page the result is TRUE/FALSE coding. Again posting real data would help us to understand your problem.

x <- as.integer(sample(3,10,rep=TRUE))
> x
 [1] 1 1 1 3 1 3 1 3 2 2
> as.dummy(x)
       [,1]  [,2]  [,3]
 [1,]  TRUE FALSE FALSE
 [2,]  TRUE FALSE FALSE
 [3,]  TRUE FALSE FALSE
 [4,] FALSE FALSE  TRUE
 [5,]  TRUE FALSE FALSE
 [6,] FALSE FALSE  TRUE
 [7,]  TRUE FALSE FALSE
 [8,] FALSE FALSE  TRUE
 [9,] FALSE  TRUE FALSE
[10,] FALSE  TRUE FALSE
attr(,"levels")
[1] "1" "2" "3"

As I understand from help page, each columns is repeated the levels(column) times and each column in result has coding T/F based on that particular factor level.

>  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?

There are only 2 clusters with levels 1 and NA. ABC belongs to cluster 1, DEF belongs to cluster NA. An what is the most weird, you have only 6 values in your db data ???

So again presenting your data either by dput or str is vital for evaluating your problem.

And BTW do not post in HTML, your messages are more or less scrambled.

Cheers
Petr


>
> Many thanks for your help.
>
> --
> Best Regards
> Matej Zuzcak
>
>
>       [[alternative HTML version deleted]]
>
> ______________________________________________
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