The process of spectral clustering
URL 'http://cran.r-project.org/src/contrib/mlbench_2.1-1.tar.gz'를 시도하고 있습니다 Content type 'application/x-gzip' length 920768 bytes (899 Kb) 열린 URL ================================================== downloaded 899 Kb * installing *source* package ‘mlbench’ ... ** 패키지 ‘mlbench’ 가 성공적으로 압축해제 되었고, MD5 sums 가 확인되었습니다 ** libs gcc -std=gnu99 -I/root/sage-5.8/local/lib/R/include -DNDEBUG -fpic -g -O2 -c waveform.c -o waveform.o gcc -std=gnu99 -shared -o mlbench.so waveform.o -L/root/sage-5.8/local/lib/R//lib -lR 다음 부분에 설치 /root/sage-5.8/local/lib/R/library/mlbench/libs ** R ** data ** inst ** preparing package for lazy loading ** help *** installing help indices ** building package indices ** testing if installed package can be loaded * DONE (mlbench) 다운로드된 소스 패키지들은 다음에 위치해 있습니다 ‘/tmp/RtmpO7DdUB/downloaded_packages’ URL 'http://cran.r-project.org/src/contrib/mlbench_2.1-1.tar.gz'를 시도하고 있습니다 Content type 'application/x-gzip' length 920768 bytes (899 Kb) 열린 URL ================================================== downloaded 899 Kb * installing *source* package ‘mlbench’ ... ** 패키지 ‘mlbench’ 가 성공적으로 압축해제 되었고, MD5 sums 가 확인되었습니다 ** libs gcc -std=gnu99 -I/root/sage-5.8/local/lib/R/include -DNDEBUG -fpic -g -O2 -c waveform.c -o waveform.o gcc -std=gnu99 -shared -o mlbench.so waveform.o -L/root/sage-5.8/local/lib/R//lib -lR 다음 부분에 설치 /root/sage-5.8/local/lib/R/library/mlbench/libs ** R ** data ** inst ** preparing package for lazy loading ** help *** installing help indices ** building package indices ** testing if installed package can be loaded * DONE (mlbench) 다운로드된 소스 패키지들은 다음에 위치해 있습니다 ‘/tmp/RtmpO7DdUB/downloaded_packages’ ![]() ![]() |
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 1.00000000 0.064179185 0.74290158 0.63193426 0.098831073 0.094897744 0.56549848 0.033550836 [2,] 0.06417919 1.000000000 0.06938066 0.04276431 0.214229495 0.275123731 0.04833520 0.008796359 [3,] 0.74290158 0.069380663 1.00000000 0.61054893 0.089569089 0.088641808 0.66577557 0.043420466 [4,] 0.63193426 0.042764307 0.61054893 1.00000000 0.062517586 0.059982837 0.71959220 0.044260673 [5,] 0.09883107 0.214229495 0.08956909 0.06251759 1.000000000 0.776556494 0.05973178 0.005091154 [6,] 0.09489774 0.275123731 0.08864181 0.05998284 0.776556494 1.000000000 0.05901605 0.005548028 [7,] 0.56549848 0.048335201 0.66577557 0.71959220 0.059731778 0.059016049 1.00000000 0.058059785 [8,] 0.03355084 0.008796359 0.04342047 0.04426067 0.005091154 0.005548028 0.05805979 1.000000000 [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 1.00000000 0.064179185 0.74290158 0.63193426 0.098831073 0.094897744 0.56549848 0.033550836 [2,] 0.06417919 1.000000000 0.06938066 0.04276431 0.214229495 0.275123731 0.04833520 0.008796359 [3,] 0.74290158 0.069380663 1.00000000 0.61054893 0.089569089 0.088641808 0.66577557 0.043420466 [4,] 0.63193426 0.042764307 0.61054893 1.00000000 0.062517586 0.059982837 0.71959220 0.044260673 [5,] 0.09883107 0.214229495 0.08956909 0.06251759 1.000000000 0.776556494 0.05973178 0.005091154 [6,] 0.09489774 0.275123731 0.08864181 0.05998284 0.776556494 1.000000000 0.05901605 0.005548028 [7,] 0.56549848 0.048335201 0.66577557 0.71959220 0.059731778 0.059016049 1.00000000 0.058059785 [8,] 0.03355084 0.008796359 0.04342047 0.04426067 0.005091154 0.005548028 0.05805979 1.000000000 |
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 1.0000000 0 0.7429016 0.6319343 0.0000000 0.0000000 0.0000000 0 [2,] 0.0000000 1 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0 [3,] 0.7429016 0 1.0000000 0.0000000 0.0000000 0.0000000 0.6657756 0 [4,] 0.6319343 0 0.0000000 1.0000000 0.0000000 0.0000000 0.7195922 0 [5,] 0.0000000 0 0.0000000 0.0000000 1.0000000 0.7765565 0.0000000 0 [6,] 0.0000000 0 0.0000000 0.0000000 0.7765565 1.0000000 0.0000000 0 [7,] 0.0000000 0 0.6657756 0.7195922 0.0000000 0.0000000 1.0000000 0 [8,] 0.0000000 0 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 1 [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 1.0000000 0 0.7429016 0.6319343 0.0000000 0.0000000 0.0000000 0 [2,] 0.0000000 1 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0 [3,] 0.7429016 0 1.0000000 0.0000000 0.0000000 0.0000000 0.6657756 0 [4,] 0.6319343 0 0.0000000 1.0000000 0.0000000 0.0000000 0.7195922 0 [5,] 0.0000000 0 0.0000000 0.0000000 1.0000000 0.7765565 0.0000000 0 [6,] 0.0000000 0 0.0000000 0.0000000 0.7765565 1.0000000 0.0000000 0 [7,] 0.0000000 0 0.6657756 0.7195922 0.0000000 0.0000000 1.0000000 0 [8,] 0.0000000 0 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 1 |
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 2.374836 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 [2,] 0.000000 2.597451 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 [3,] 0.000000 0.000000 2.408677 0.000000 0.000000 0.000000 0.000000 0.000000 [4,] 0.000000 0.000000 0.000000 2.351526 0.000000 0.000000 0.000000 0.000000 [5,] 0.000000 0.000000 0.000000 0.000000 2.523175 0.000000 0.000000 0.000000 [6,] 0.000000 0.000000 0.000000 0.000000 0.000000 2.519936 0.000000 0.000000 [7,] 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.170424 0.000000 [8,] 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.302241 [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 2.374836 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 [2,] 0.000000 2.597451 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 [3,] 0.000000 0.000000 2.408677 0.000000 0.000000 0.000000 0.000000 0.000000 [4,] 0.000000 0.000000 0.000000 2.351526 0.000000 0.000000 0.000000 0.000000 [5,] 0.000000 0.000000 0.000000 0.000000 2.523175 0.000000 0.000000 0.000000 [6,] 0.000000 0.000000 0.000000 0.000000 0.000000 2.519936 0.000000 0.000000 [7,] 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.170424 0.000000 [8,] 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.302241 |
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [1,] 1.4 0.0 -0.7 -0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 [2,] 0.0 1.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 [3,] -0.7 0.0 1.4 0.0 0.0 0.0 -0.7 0.0 0.0 0.0 0.0 0.0 [4,] -0.6 0.0 0.0 1.4 0.0 0.0 -0.7 0.0 0.0 0.0 0.0 0.0 [5,] 0.0 0.0 0.0 0.0 1.5 -0.8 0.0 0.0 0.0 0.0 0.0 0.0 [6,] 0.0 0.0 0.0 0.0 -0.8 1.5 0.0 0.0 0.0 0.0 0.0 0.0 [7,] 0.0 0.0 -0.7 -0.7 0.0 0.0 2.2 0.0 0.0 -0.8 0.0 0.0 [8,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.3 0.0 0.0 0.0 0.0 [9,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.5 0.0 0.0 0.0 [10,] 0.0 0.0 0.0 0.0 0.0 0.0 -0.8 0.0 0.0 1.6 -0.8 0.0 [11,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.8 1.5 -0.8 [12,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.8 1.5 [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [1,] 1.4 0.0 -0.7 -0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 [2,] 0.0 1.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 [3,] -0.7 0.0 1.4 0.0 0.0 0.0 -0.7 0.0 0.0 0.0 0.0 0.0 [4,] -0.6 0.0 0.0 1.4 0.0 0.0 -0.7 0.0 0.0 0.0 0.0 0.0 [5,] 0.0 0.0 0.0 0.0 1.5 -0.8 0.0 0.0 0.0 0.0 0.0 0.0 [6,] 0.0 0.0 0.0 0.0 -0.8 1.5 0.0 0.0 0.0 0.0 0.0 0.0 [7,] 0.0 0.0 -0.7 -0.7 0.0 0.0 2.2 0.0 0.0 -0.8 0.0 0.0 [8,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.3 0.0 0.0 0.0 0.0 [9,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.5 0.0 0.0 0.0 [10,] 0.0 0.0 0.0 0.0 0.0 0.0 -0.8 0.0 0.0 1.6 -0.8 0.0 [11,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.8 1.5 -0.8 [12,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.8 1.5 |
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [1,] 0.6 0.0 -0.3 -0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 [2,] 0.0 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 [3,] -0.3 0.0 0.6 0.0 0.0 0.0 -0.3 0.0 0.0 0.0 0.0 0.0 [4,] -0.3 0.0 0.0 0.6 0.0 0.0 -0.3 0.0 0.0 0.0 0.0 0.0 [5,] 0.0 0.0 0.0 0.0 0.6 -0.3 0.0 0.0 0.0 0.0 0.0 0.0 [6,] 0.0 0.0 0.0 0.0 -0.3 0.6 0.0 0.0 0.0 0.0 0.0 0.0 [7,] 0.0 0.0 -0.2 -0.2 0.0 0.0 0.7 0.0 0.0 -0.2 0.0 0.0 [8,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 0.0 0.0 [9,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 0.0 [10,] 0.0 0.0 0.0 0.0 0.0 0.0 -0.3 0.0 0.0 0.6 -0.3 0.0 [11,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.3 0.6 -0.3 [12,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.3 0.6 [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [1,] 0.6 0.0 -0.3 -0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 [2,] 0.0 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 [3,] -0.3 0.0 0.6 0.0 0.0 0.0 -0.3 0.0 0.0 0.0 0.0 0.0 [4,] -0.3 0.0 0.0 0.6 0.0 0.0 -0.3 0.0 0.0 0.0 0.0 0.0 [5,] 0.0 0.0 0.0 0.0 0.6 -0.3 0.0 0.0 0.0 0.0 0.0 0.0 [6,] 0.0 0.0 0.0 0.0 -0.3 0.6 0.0 0.0 0.0 0.0 0.0 0.0 [7,] 0.0 0.0 -0.2 -0.2 0.0 0.0 0.7 0.0 0.0 -0.2 0.0 0.0 [8,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 0.0 0.0 [9,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 0.0 [10,] 0.0 0.0 0.0 0.0 0.0 0.0 -0.3 0.0 0.0 0.6 -0.3 0.0 [11,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.3 0.6 -0.3 [12,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.3 0.6 |
경고 메시지가 손실되었습니다 In xy.coords(x, y, xlabel, ylabel, log) : 1 y value <= 0 omitted from logarithmic plot 경고 메시지가 손실되었습니다 In xy.coords(x, y, xlabel, ylabel, log) : 1 y value <= 0 omitted from logarithmic plot 경고 메시지가 손실되었습니다 In xy.coords(x, y, xlabel, ylabel, log) : 1 y value <= 0 omitted from logarithmic plot 경고 메시지가 손실되었습니다 In xy.coords(x, y, xlabel, ylabel, log) : 1 y value <= 0 omitted from logarithmic plot ![]() ![]() |
경고 메시지가 손실되었습니다 In xy.coords(x, y, xlabel, ylabel, log) : 1 y value <= 0 omitted from logarithmic plot 경고 메시지가 손실되었습니다 In xy.coords(x, y, xlabel, ylabel, log) : 1 y value <= 0 omitted from logarithmic plot 경고 메시지가 손실되었습니다 In xy.coords(x, y, xlabel, ylabel, log) : 1 y value <= 0 omitted from logarithmic plot 경고 메시지가 손실되었습니다 In xy.coords(x, y, xlabel, ylabel, log) : 1 y value <= 0 omitted from logarithmic plot ![]() ![]() |
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Compare with K-means Clustering
K-means clustering with 2 clusters of sizes 48, 52 Cluster means: [,1] [,2] 1 1.077452 -1.504055 2 -1.027031 1.371337 Clustering vector: [1] 1 1 1 1 1 1 1 2 1 1 2 2 2 1 1 2 2 2 2 2 1 2 1 2 1 1 1 2 2 1 2 2 2 2 1 2 2 1 2 2 2 2 1 2 2 2 2 [48] 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 1 1 1 2 2 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 1 2 1 1 [95] 1 2 1 2 1 1 Within cluster sum of squares by cluster: [1] 207.0643 240.7847 (between_SS / total_SS = 41.4 %) Available components: [1] "cluster" "centers" "totss" "withinss" "tot.withinss" "betweenss" [7] "size" K-means clustering with 2 clusters of sizes 48, 52 Cluster means: [,1] [,2] 1 1.077452 -1.504055 2 -1.027031 1.371337 Clustering vector: [1] 1 1 1 1 1 1 1 2 1 1 2 2 2 1 1 2 2 2 2 2 1 2 1 2 1 1 1 2 2 1 2 2 2 2 1 2 2 1 2 2 2 2 1 2 2 2 2 [48] 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 1 1 1 2 2 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 1 2 1 1 [95] 1 2 1 2 1 1 Within cluster sum of squares by cluster: [1] 207.0643 240.7847 (between_SS / total_SS = 41.4 %) Available components: [1] "cluster" "centers" "totss" "withinss" "tot.withinss" "betweenss" [7] "size" ![]() ![]() |
K-means clustering with 3 clusters of sizes 34, 32, 34 Cluster means: [,1] [,2] 1 -0.2995602 2.183563 2 -1.7926388 -1.054059 3 1.9371052 -1.217540 Clustering vector: [1] 3 2 3 3 3 2 3 1 2 3 1 1 1 3 3 1 1 1 1 1 3 1 3 1 3 3 3 1 1 3 1 1 1 1 3 1 2 3 1 2 2 1 3 1 1 2 1 [48] 1 3 2 2 1 2 2 2 2 3 2 2 2 2 2 1 2 2 1 2 1 2 2 2 2 1 3 2 2 2 2 3 3 3 3 1 3 3 3 1 3 1 3 3 1 3 3 [95] 2 1 2 2 3 3 Within cluster sum of squares by cluster: [1] 98.27141 86.32112 98.67226 (between_SS / total_SS = 63.0 %) Available components: [1] "cluster" "centers" "totss" "withinss" "tot.withinss" "betweenss" [7] "size" K-means clustering with 3 clusters of sizes 34, 32, 34 Cluster means: [,1] [,2] 1 -0.2995602 2.183563 2 -1.7926388 -1.054059 3 1.9371052 -1.217540 Clustering vector: [1] 3 2 3 3 3 2 3 1 2 3 1 1 1 3 3 1 1 1 1 1 3 1 3 1 3 3 3 1 1 3 1 1 1 1 3 1 2 3 1 2 2 1 3 1 1 2 1 [48] 1 3 2 2 1 2 2 2 2 3 2 2 2 2 2 1 2 2 1 2 1 2 2 2 2 1 3 2 2 2 2 3 3 3 3 1 3 3 3 1 3 1 3 3 1 3 3 [95] 2 1 2 2 3 3 Within cluster sum of squares by cluster: [1] 98.27141 86.32112 98.67226 (between_SS / total_SS = 63.0 %) Available components: [1] "cluster" "centers" "totss" "withinss" "tot.withinss" "betweenss" [7] "size" ![]() ![]() |
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