[R] Clustering of datasets

[Subhamitra Patra]

Dear all,

I also tried the k-mean method in some other parts of my data, but still
not getting the perfect result as expected.

Herewith I attached the related code as below. Please suggest to me where I
am lacking in my below code.

 DMs<-read.table(text="Country Data
                 Israel 0.087320199
                Bahrein 0.37991129
              HongKong 0.037552721
                  Japan 0.235350891
                Kuwait 0.286427554
                  oman 0.400096249
                  Qatar 0.270693298
            SouthKorea 0.007407618
            SaudiArabia 0.187578553
              Singapore 0.008528448
                Taiwan 0.027371676
                    UAE 0.276795224
                Austria 0.015132794
                Belgium 0.008513907
                Cyprus  -0.000938601
          CzechRepublic 0.017460065
                Denmark 0.029490066
                Estonia 0.114144041
                Finland 0.016245116
                France 0.007217465
                Germany 0.00371948
                Greece -0.008527501
                Iceland 0.748097785
                Ireland 0.023309721
                Latvia 0.178227267
              Lithuania 0.100033752
              Luxemborg 0.044546393
                  Malta 0.128679817
            Netherland 0.010188604
                Norway 0.003437861
                Poland 0.006426383
              Portugal 0.00753412
              Slovakia 0.505992775
              Slovenia 0.162475815
                  Spain 0.00267973
                Sweden 0.009967609
            Switzerland 0.020557185
                    UK 0.009340789
                Hungary 0.005389885
                Canada -0.000531982
                  Chile 0.007080471
                    USA 0.013516878
                Bermuda -0.338491435
              Australia 0.113039242
            Newzealand 0.154508239",
                 header = TRUE,stringsAsFactors=FALSE)
library(cluster)
k1<-kmeans(DMs[,2],centers=2,nstart=25)
plot(DMs[,2],col=k1$cluster,pch=19,xlim=c(1,45), ylim=c(-0.001,2.5))
text(1:45+0.5,DMs[,2]+0.05,DMs[,1],col=k1$cluster)
legend(2,1,c("cluster 1: Highly efficient DMs","cluster 2: Less efficient
DMs"),
       col=1:5,pch=19)

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05:34:10 PM

On Mon, Sep 5, 2022 at 5:01 PM Subhamitra Patra <subhamitra.patra using gmail.com>
wrote:

> Dear all,
>
> I am about to cluster my datasets by using K-mean clustering techniques in
> R, but getting some type of scattered results. Herewith I pasted my code
> below. Please suggest to me where I am lacking in my code. I was pasting my
> data before applying the K-mean method as follows.
>
> DMs<-read.table(text="Country DATA
>                       IS -0.0092
>                       BA -0.0235
>                       HK -0.0239
>                       JA -0.0333
>                       KU -0.0022
>                       OM -0.0963
>                       QA -0.0706
>                       SK -0.0322
>                       SA -0.1233
>                       SI -0.0141
>                       TA -0.0142
>                       UAE -0.0656
>                       AUS -0.0230
>                      BEL -0.0006
>                      CYP -0.0085
>                      CR  -0.0398
>                     DEN  -0.0423
>                       EST -0.0604
>                       FIN -0.0227
>                       FRA -0.0085
>                      GER -0.0272
>                      GrE -0.3519
>                      ICE -0.0210
>                      IRE -0.0057
>                      LAT -0.0595
>                     LITH -0.0451
>                     LUXE -0.0023
>                     MAL  -0.0351
>                     NETH -0.0048
>                       NOR -0.0495
>                       POL -0.0081
>                     PORT -0.0044
>                     SLOVA -0.1210
>                     SLOVE -0.0031
>                       SPA -0.0213
>                       SWE -0.0106
>                     SWIT -0.0152
>                       UK -0.0030
>                     HUNG -0.0086
>                       CAN -0.0144
>                     CHIL -0.0078
>                       USA -0.0042
>                     BERM -0.0035
>                     AUST -0.0211
>                     NEWZ -0.0538" ,
>                  header = TRUE,stringsAsFactors=FALSE)
> library(cluster)
> k1<-kmeans(DMs[,2],centers=2,nstart=25)
> plot(DMs[,2],col=k1$cluster,pch=19,xlim=c(1,46), ylim=c(-0.12,0))
> text(1:46,DMs[,2],DMs[,1],col=k1$cluster)
> legend(10,1,c("cluster 1: Highly Integrated","cluster 2: Less Integrated"),
> col=1:2,pch=19)
>
>
> --
> *Best Regards,*
> *Subhamitra Patra*
> *Phd. Research Scholar*
> *Department of Humanities and Social Sciences*
> *Indian Institute of Technology, Kharagpur*
> *INDIA*
>
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> 04:55:22 PM
>


-- 
*Best Regards,*
*Subhamitra Patra*
*Phd. Research Scholar*
*Department of Humanities and Social Sciences*
*Indian Institute of Technology, Kharagpur*
*INDIA*

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