CLUSTERING
Kekila Akmal Nifcky
2026-02-24
Reading Data
Pertama, download data dari link dataset yang sudah disediakan. Selanjutnya, import dataset ke dalam variabel data.
data__ <- read.csv("D:/Semester 4/data11.csv")
head(data__)## StationId Date PM2.5 PM10 NO NO2 NOx NH3 CO SO2 O3
## 1 AP001 2017-11-24 71.36 115.75 1.75 20.65 12.40 12.19 0.10 10.76 109.26
## 2 AP001 2017-11-25 81.40 124.50 1.44 20.50 12.08 10.72 0.12 15.24 127.09
## 3 AP001 2017-11-26 78.32 129.06 1.26 26.00 14.85 10.28 0.14 26.96 117.44
## 4 AP001 2017-11-27 88.76 135.32 6.60 30.85 21.77 12.91 0.11 33.59 111.81
## 5 AP001 2017-11-28 64.18 104.09 2.56 28.07 17.01 11.42 0.09 19.00 138.18
## 6 AP001 2017-11-29 72.47 114.84 5.23 23.20 16.59 12.25 0.16 10.55 109.74
## Benzene Toluene Xylene AQI AQI_Bucket
## 1 0.17 5.92 0.10 NA
## 2 0.20 6.50 0.06 184 Moderate
## 3 0.22 7.95 0.08 197 Moderate
## 4 0.29 7.63 0.12 198 Moderate
## 5 0.17 5.02 0.07 188 Moderate
## 6 0.21 4.71 0.08 173 ModerateImport Library
Import library esensial untuk memudahkan proses analisis
library(tidyverse)## Warning: package 'tidyverse' was built under R version 4.5.3## Warning: package 'readr' was built under R version 4.5.3## Warning: package 'forcats' was built under R version 4.5.3## Warning: package 'lubridate' was built under R version 4.5.3## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.2.0 ✔ readr 2.2.0
## ✔ forcats 1.0.1 ✔ stringr 1.6.0
## ✔ ggplot2 4.0.2 ✔ tibble 3.3.1
## ✔ lubridate 1.9.5 ✔ tidyr 1.3.2
## ✔ purrr 1.2.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(flexclust)## Warning: package 'flexclust' was built under R version 4.5.3library(dbscan)## Warning: package 'dbscan' was built under R version 4.5.3##
## Attaching package: 'dbscan'
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## The following object is masked from 'package:stats':
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## as.dendrogramlibrary(meanShiftR)
library(e1071)## Warning: package 'e1071' was built under R version 4.5.3##
## Attaching package: 'e1071'
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## The following object is masked from 'package:flexclust':
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## bclust
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## The following object is masked from 'package:ggplot2':
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## elementlibrary(cluster)## Warning: package 'cluster' was built under R version 4.5.3library(fpc)## Warning: package 'fpc' was built under R version 4.5.3##
## Attaching package: 'fpc'
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## The following object is masked from 'package:dbscan':
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## dbscanlibrary(mclust)## Warning: package 'mclust' was built under R version 4.5.3## Package 'mclust' version 6.1.2
## Type 'citation("mclust")' for citing this R package in publications.
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## Attaching package: 'mclust'
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## count
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## mapPreprocessing
Tahap pertama yang dilakukan adalah memilah atau subset variabel yang bukan numerik.
str(data__)## 'data.frame': 108035 obs. of 16 variables:
## $ StationId : chr "AP001" "AP001" "AP001" "AP001" ...
## $ Date : chr "2017-11-24" "2017-11-25" "2017-11-26" "2017-11-27" ...
## $ PM2.5 : num 71.4 81.4 78.3 88.8 64.2 ...
## $ PM10 : num 116 124 129 135 104 ...
## $ NO : num 1.75 1.44 1.26 6.6 2.56 5.23 4.69 4.58 7.71 0.97 ...
## $ NO2 : num 20.6 20.5 26 30.9 28.1 ...
## $ NOx : num 12.4 12.1 14.8 21.8 17 ...
## $ NH3 : num 12.2 10.7 10.3 12.9 11.4 ...
## $ CO : num 0.1 0.12 0.14 0.11 0.09 0.16 0.12 0.1 0.1 0.15 ...
## $ SO2 : num 10.8 15.2 27 33.6 19 ...
## $ O3 : num 109 127 117 112 138 ...
## $ Benzene : num 0.17 0.2 0.22 0.29 0.17 0.21 0.16 0.17 0.25 0.23 ...
## $ Toluene : num 5.92 6.5 7.95 7.63 5.02 4.71 3.52 2.85 2.79 3.82 ...
## $ Xylene : num 0.1 0.06 0.08 0.12 0.07 0.08 0.06 0.04 0.07 0.04 ...
## $ AQI : num NA 184 197 198 188 173 165 191 191 227 ...
## $ AQI_Bucket: chr "" "Moderate" "Moderate" "Moderate" ...data_NUM <- data__[, sapply(data__, is.numeric)]str(data_NUM)## 'data.frame': 108035 obs. of 13 variables:
## $ PM2.5 : num 71.4 81.4 78.3 88.8 64.2 ...
## $ PM10 : num 116 124 129 135 104 ...
## $ NO : num 1.75 1.44 1.26 6.6 2.56 5.23 4.69 4.58 7.71 0.97 ...
## $ NO2 : num 20.6 20.5 26 30.9 28.1 ...
## $ NOx : num 12.4 12.1 14.8 21.8 17 ...
## $ NH3 : num 12.2 10.7 10.3 12.9 11.4 ...
## $ CO : num 0.1 0.12 0.14 0.11 0.09 0.16 0.12 0.1 0.1 0.15 ...
## $ SO2 : num 10.8 15.2 27 33.6 19 ...
## $ O3 : num 109 127 117 112 138 ...
## $ Benzene: num 0.17 0.2 0.22 0.29 0.17 0.21 0.16 0.17 0.25 0.23 ...
## $ Toluene: num 5.92 6.5 7.95 7.63 5.02 4.71 3.52 2.85 2.79 3.82 ...
## $ Xylene : num 0.1 0.06 0.08 0.12 0.07 0.08 0.06 0.04 0.07 0.04 ...
## $ AQI : num NA 184 197 198 188 173 165 191 191 227 ...Menghapus baris yang terdeteksi memiliki nilai kosong.
for(i in 1:ncol(data_NUM)){
data_NUM[is.na(data_NUM[,i]), i] <- mean(data_NUM[,i], na.rm = TRUE)
}set.seed(123)
data_sample <- data_NUM[sample(nrow(data_NUM), 1000), ]sum(is.na(data_sample))## [1] 0distribusi data
library(ggplot2)
data_long <- data_sample %>%
pivot_longer(cols = everything(),
names_to = "Variable",
values_to = "Value")
ggplot(data_long, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", color = "black") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
labs(title = "Boxplot Masing-Masing Variabel",
x = "Variabel",
y = "Nilai")
scale data untuk memastikan bahwa metrics jarak tidak bias
data_scaled <- scale(data_sample)mencari jumlah cluster (k) untuk k-means menggunakan elbow method
# Elbow Method using base R and a loop
wss <- sapply(1:10, function(k){
kmeans(data_scaled, centers = k, nstart = 20)$tot.withinss
})
par(mfrow = c(1, 1))
plot(1:10, wss, type = "b", pch = 19, frame = FALSE,
xlab = "Number of clusters K",
ylab = "Total within-clusters sum of squares",
main = "Elbow Method")
avg_sil <- function(k) {
km_res <- kmeans(data_scaled, centers = k, nstart = 25)
ss <- silhouette(km_res$cluster, dist(data_scaled))
mean(ss[, 3])
}
k_values <- 2:10
avg_sil_values <- sapply(k_values, avg_sil)
par(mfrow = c(1, 1))
plot(k_values, avg_sil_values, type = "b", pch = 19, frame = FALSE,
xlab = "Number of clusters K",
ylab = "Average Silhouette Width",
main = "Silhouette Analysis")
datates <- data_scaled[, c("AQI", "PM2.5")]Kmeans
km_res <- kmeans(data_scaled, centers = 3)visualisasi
plot(datates, col = km_res$cluster, main = "K-means")
kmedian
# --- 2. K-median ---
# Using flexclust; 'kcca' is the general function for centroid-based clustering
kmed_res <- kcca(data_scaled, k = 3, family = kccaFamily("kmedians"))## Found more than one class "kcca" in cache; using the first, from namespace 'flexclust'## Also defined by 'kernlab'## Found more than one class "kcca" in cache; using the first, from namespace 'flexclust'## Also defined by 'kernlab'visualisasi
plot(datates, col = clusters(kmed_res), main = "K-medians")
DBSCAN
db_res <- dbscan(data_scaled, eps = 1, MinPts = 15)visualisasi
plot(datates, col = db_res$cluster + 1L, main = "DBSCAN")
mean shift
ms_res <- meanShift(data_scaled)visualisasi
plot(datates, col = ms_res$assignment, main = "Mean Shift")
fuzzy c-means
fcm_res <- cmeans(data_scaled, centers = 3, m = 2) # m = 2 is the fuzziness parametervisualisasi
plot(datates, col = fcm_res$cluster, main = "Fuzzy C-means")
km_res$centers## PM2.5 PM10 NO NO2 NOx NH3 CO
## 1 2.4920725 2.5757612 2.7703622 2.1847392 2.6223440 1.5343878 0.3312041
## 2 0.3898740 0.3253367 0.1893929 0.3585502 0.3004405 0.1267733 0.2341986
## 3 -0.5084961 -0.4714539 -0.3951667 -0.4574681 -0.4585225 -0.2341171 -0.1947259
## SO2 O3 Benzene Toluene Xylene AQI
## 1 0.5131853 0.48377170 1.4307127 1.7908173 0.08719201 2.2872285
## 2 0.2534683 0.03544812 0.1339228 0.1423602 0.14611621 0.5451632
## 3 -0.2254444 -0.07066168 -0.2292540 -0.2693395 -0.11014405 -0.5972968kmed_res@centers## PM2.5 PM10 NO NO2 NOx NH3
## [1,] -0.82305878 -1.08423789 -0.55385419 -0.786460097 -0.55609102 -0.926705452
## [2,] 0.01747389 0.00479915 -0.01682686 -0.004734821 -0.00702352 -0.002394755
## [3,] -0.49633105 0.00479915 -0.54500465 -0.506495804 -0.52511374 -0.002394755
## CO SO2 O3 Benzene Toluene Xylene
## [1,] -0.28208013 -0.343665550 -0.441358246 -0.26680634 -7.621613e-05 0.04018485
## [2,] -0.01279538 -0.004629688 0.004486845 0.02992548 -7.621613e-05 0.04018485
## [3,] -0.21973341 -0.404582582 0.004486845 -0.46222882 -5.654928e-01 0.04018485
## AQI
## [1,] -0.91180608
## [2,] 0.03358787
## [3,] -0.60834417db_res$cluster## [1] 1 1 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1 0 0 2 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0
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## [1000] 1ms_res$assignment## [,1]
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## [413,] 1
## [414,] 1
## [415,] 1
## [416,] 1
## [417,] 4
## [418,] 43
## [419,] 4
## [420,] 1
## [421,] 1
## [422,] 4
## [423,] 1
## [424,] 25
## [425,] 44
## [426,] 1
## [427,] 1
## [428,] 8
## [429,] 45
## [430,] 1
## [431,] 1
## [432,] 4
## [433,] 1
## [434,] 46
## [435,] 8
## [436,] 1
## [437,] 1
## [438,] 4
## [439,] 1
## [440,] 4
## [441,] 1
## [442,] 1
## [443,] 1
## [444,] 1
## [445,] 1
## [446,] 8
## [447,] 1
## [448,] 1
## [449,] 1
## [450,] 4
## [451,] 1
## [452,] 47
## [453,] 1
## [454,] 4
## [455,] 48
## [456,] 1
## [457,] 1
## [458,] 1
## [459,] 1
## [460,] 1
## [461,] 1
## [462,] 1
## [463,] 1
## [464,] 1
## [465,] 4
## [466,] 1
## [467,] 1
## [468,] 1
## [469,] 1
## [470,] 1
## [471,] 1
## [472,] 1
## [473,] 1
## [474,] 1
## [475,] 8
## [476,] 1
## [477,] 1
## [478,] 4
## [479,] 4
## [480,] 49
## [481,] 25
## [482,] 50
## [483,] 4
## [484,] 1
## [485,] 1
## [486,] 1
## [487,] 4
## [488,] 1
## [489,] 1
## [490,] 1
## [491,] 1
## [492,] 1
## [493,] 1
## [494,] 1
## [495,] 1
## [496,] 1
## [497,] 25
## [498,] 1
## [499,] 4
## [500,] 4
## [501,] 1
## [502,] 1
## [503,] 1
## [504,] 1
## [505,] 51
## [506,] 1
## [507,] 4
## [508,] 1
## [509,] 1
## [510,] 4
## [511,] 1
## [512,] 4
## [513,] 1
## [514,] 1
## [515,] 1
## [516,] 1
## [517,] 25
## [518,] 52
## [519,] 4
## [520,] 1
## [521,] 53
## [522,] 1
## [523,] 1
## [524,] 8
## [525,] 4
## [526,] 54
## [527,] 1
## [528,] 1
## [529,] 1
## [530,] 1
## [531,] 1
## [532,] 1
## [533,] 4
## [534,] 55
## [535,] 1
## [536,] 1
## [537,] 56
## [538,] 1
## [539,] 1
## [540,] 1
## [541,] 1
## [542,] 1
## [543,] 1
## [544,] 4
## [545,] 57
## [546,] 4
## [547,] 1
## [548,] 58
## [549,] 1
## [550,] 1
## [551,] 1
## [552,] 1
## [553,] 1
## [554,] 4
## [555,] 1
## [556,] 8
## [557,] 1
## [558,] 8
## [559,] 59
## [560,] 1
## [561,] 1
## [562,] 60
## [563,] 1
## [564,] 4
## [565,] 1
## [566,] 1
## [567,] 1
## [568,] 4
## [569,] 1
## [570,] 1
## [571,] 1
## [572,] 1
## [573,] 1
## [574,] 1
## [575,] 1
## [576,] 61
## [577,] 1
## [578,] 1
## [579,] 1
## [580,] 4
## [581,] 1
## [582,] 1
## [583,] 1
## [584,] 62
## [585,] 1
## [586,] 1
## [587,] 1
## [588,] 4
## [589,] 1
## [590,] 1
## [591,] 63
## [592,] 4
## [593,] 64
## [594,] 1
## [595,] 1
## [596,] 1
## [597,] 1
## [598,] 1
## [599,] 1
## [600,] 1
## [601,] 65
## [602,] 33
## [603,] 1
## [604,] 1
## [605,] 1
## [606,] 1
## [607,] 1
## [608,] 1
## [609,] 66
## [610,] 1
## [611,] 1
## [612,] 1
## [613,] 67
## [614,] 1
## [615,] 1
## [616,] 1
## [617,] 4
## [618,] 1
## [619,] 1
## [620,] 1
## [621,] 1
## [622,] 1
## [623,] 4
## [624,] 4
## [625,] 1
## [626,] 1
## [627,] 8
## [628,] 1
## [629,] 1
## [630,] 68
## [631,] 1
## [632,] 4
## [633,] 1
## [634,] 4
## [635,] 1
## [636,] 1
## [637,] 1
## [638,] 1
## [639,] 4
## [640,] 1
## [641,] 1
## [642,] 1
## [643,] 1
## [644,] 1
## [645,] 1
## [646,] 4
## [647,] 1
## [648,] 1
## [649,] 1
## [650,] 1
## [651,] 1
## [652,] 63
## [653,] 1
## [654,] 69
## [655,] 1
## [656,] 1
## [657,] 70
## [658,] 1
## [659,] 1
## [660,] 1
## [661,] 1
## [662,] 1
## [663,] 1
## [664,] 1
## [665,] 4
## [666,] 4
## [667,] 4
## [668,] 4
## [669,] 1
## [670,] 1
## [671,] 1
## [672,] 4
## [673,] 4
## [674,] 4
## [675,] 71
## [676,] 1
## [677,] 1
## [678,] 72
## [679,] 1
## [680,] 1
## [681,] 1
## [682,] 1
## [683,] 1
## [684,] 1
## [685,] 1
## [686,] 73
## [687,] 1
## [688,] 74
## [689,] 1
## [690,] 1
## [691,] 1
## [692,] 1
## [693,] 1
## [694,] 1
## [695,] 1
## [696,] 1
## [697,] 1
## [698,] 1
## [699,] 1
## [700,] 1
## [701,] 1
## [702,] 75
## [703,] 1
## [704,] 1
## [705,] 1
## [706,] 1
## [707,] 1
## [708,] 1
## [709,] 1
## [710,] 1
## [711,] 1
## [712,] 1
## [713,] 1
## [714,] 1
## [715,] 1
## [716,] 4
## [717,] 1
## [718,] 8
## [719,] 1
## [720,] 76
## [721,] 77
## [722,] 78
## [723,] 1
## [724,] 1
## [725,] 8
## [726,] 1
## [727,] 1
## [728,] 4
## [729,] 1
## [730,] 79
## [731,] 1
## [732,] 1
## [733,] 1
## [734,] 1
## [735,] 80
## [736,] 1
## [737,] 4
## [738,] 25
## [739,] 1
## [740,] 1
## [741,] 1
## [742,] 1
## [743,] 4
## [744,] 1
## [745,] 4
## [746,] 1
## [747,] 1
## [748,] 8
## [749,] 81
## [750,] 1
## [751,] 1
## [752,] 1
## [753,] 1
## [754,] 1
## [755,] 4
## [756,] 1
## [757,] 1
## [758,] 82
## [759,] 83
## [760,] 1
## [761,] 4
## [762,] 84
## [763,] 1
## [764,] 1
## [765,] 1
## [766,] 1
## [767,] 4
## [768,] 4
## [769,] 1
## [770,] 85
## [771,] 4
## [772,] 1
## [773,] 1
## [774,] 1
## [775,] 1
## [776,] 4
## [777,] 1
## [778,] 1
## [779,] 1
## [780,] 1
## [781,] 1
## [782,] 80
## [783,] 1
## [784,] 25
## [785,] 86
## [786,] 1
## [787,] 1
## [788,] 1
## [789,] 1
## [790,] 8
## [791,] 1
## [792,] 1
## [793,] 1
## [794,] 4
## [795,] 1
## [796,] 1
## [797,] 4
## [798,] 1
## [799,] 1
## [800,] 4
## [801,] 1
## [802,] 4
## [803,] 1
## [804,] 87
## [805,] 1
## [806,] 1
## [807,] 1
## [808,] 1
## [809,] 1
## [810,] 1
## [811,] 1
## [812,] 1
## [813,] 1
## [814,] 1
## [815,] 1
## [816,] 4
## [817,] 1
## [818,] 4
## [819,] 88
## [820,] 1
## [821,] 1
## [822,] 1
## [823,] 89
## [824,] 90
## [825,] 91
## [826,] 1
## [827,] 1
## [828,] 92
## [829,] 1
## [830,] 93
## [831,] 94
## [832,] 1
## [833,] 95
## [834,] 96
## [835,] 1
## [836,] 4
## [837,] 1
## [838,] 4
## [839,] 1
## [840,] 1
## [841,] 46
## [842,] 4
## [843,] 1
## [844,] 4
## [845,] 1
## [846,] 97
## [847,] 1
## [848,] 1
## [849,] 1
## [850,] 4
## [851,] 4
## [852,] 4
## [853,] 1
## [854,] 1
## [855,] 1
## [856,] 4
## [857,] 1
## [858,] 98
## [859,] 1
## [860,] 1
## [861,] 1
## [862,] 1
## [863,] 1
## [864,] 99
## [865,] 1
## [866,] 100
## [867,] 4
## [868,] 4
## [869,] 1
## [870,] 4
## [871,] 4
## [872,] 1
## [873,] 1
## [874,] 101
## [875,] 1
## [876,] 4
## [877,] 4
## [878,] 1
## [879,] 8
## [880,] 1
## [881,] 1
## [882,] 1
## [883,] 1
## [884,] 1
## [885,] 1
## [886,] 1
## [887,] 1
## [888,] 1
## [889,] 1
## [890,] 1
## [891,] 1
## [892,] 8
## [893,] 63
## [894,] 1
## [895,] 1
## [896,] 4
## [897,] 8
## [898,] 1
## [899,] 1
## [900,] 94
## [901,] 1
## [902,] 102
## [903,] 1
## [904,] 1
## [905,] 1
## [906,] 1
## [907,] 1
## [908,] 1
## [909,] 8
## [910,] 97
## [911,] 8
## [912,] 4
## [913,] 1
## [914,] 1
## [915,] 1
## [916,] 103
## [917,] 1
## [918,] 104
## [919,] 4
## [920,] 1
## [921,] 105
## [922,] 1
## [923,] 1
## [924,] 1
## [925,] 1
## [926,] 106
## [927,] 1
## [928,] 25
## [929,] 1
## [930,] 1
## [931,] 1
## [932,] 1
## [933,] 1
## [934,] 1
## [935,] 1
## [936,] 1
## [937,] 1
## [938,] 1
## [939,] 1
## [940,] 1
## [941,] 1
## [942,] 1
## [943,] 8
## [944,] 1
## [945,] 4
## [946,] 1
## [947,] 1
## [948,] 1
## [949,] 4
## [950,] 4
## [951,] 4
## [952,] 1
## [953,] 1
## [954,] 1
## [955,] 1
## [956,] 1
## [957,] 60
## [958,] 1
## [959,] 1
## [960,] 1
## [961,] 1
## [962,] 1
## [963,] 1
## [964,] 1
## [965,] 107
## [966,] 1
## [967,] 1
## [968,] 4
## [969,] 1
## [970,] 1
## [971,] 1
## [972,] 1
## [973,] 108
## [974,] 1
## [975,] 4
## [976,] 1
## [977,] 1
## [978,] 1
## [979,] 4
## [980,] 109
## [981,] 1
## [982,] 1
## [983,] 8
## [984,] 1
## [985,] 1
## [986,] 4
## [987,] 4
## [988,] 1
## [989,] 1
## [990,] 1
## [991,] 1
## [992,] 4
## [993,] 110
## [994,] 1
## [995,] 4
## [996,] 1
## [997,] 1
## [998,] 1
## [999,] 1
## [1000,] 1fcm_res$cluster## 51663 57870 2986 29925 95246 103065 68293 62555 45404 65161 46435
## 2 1 1 2 2 3 2 1 1 1 1
## 104474 9642 59134 52132 96849 14183 15180 27168 89709 9097 30538
## 2 1 1 2 1 2 1 2 1 2 2
## 56219 94517 7989 13536 90077 6216 83519 29394 53241 28825 106773
## 2 2 2 1 3 1 1 2 1 2 2
## 41 14426 105695 72820 51656 94038 58527 77009 43042 77837 6134
## 1 2 2 1 2 1 1 1 3 2 1
## 33523 21812 39895 9640 85278 9326 26510 20960 14403 64502 71503
## 3 2 1 1 1 2 3 2 2 1 2
## 45221 94335 92372 77585 80686 70563 32606 16152 25559 14215 14287
## 2 1 1 1 1 1 1 2 3 2 2
## 23194 90094 34976 14491 82949 77584 40503 34724 103662 86013 17369
## 2 1 1 2 1 2 3 3 1 1 1
## 31542 102537 59106 86605 40632 96111 43204 37544 99289 84427 76820
## 2 3 1 1 1 2 2 2 2 1 1
## 82115 44196 92337 44983 91438 36717 28078 69369 91564 43406 41488
## 1 1 1 2 2 1 1 1 2 3 2
## 47485 63528 14536 83069 51465 26503 103319 88299 32953 413 10762
## 2 1 2 3 1 3 1 2 3 2 2
## 48182 30571 42521 74522 14745 25946 80340 43928 6601 57701 53518
## 3 2 2 1 2 2 2 3 3 1 2
## 72326 52353 66154 47802 31517 66075 32263 95989 69161 81118 56157
## 2 3 1 1 2 1 2 2 1 1 1
## 19392 46137 67747 2286 59970 84298 54661 32281 107575 64085 7826
## 2 2 2 1 1 1 1 1 1 2 3
## 80287 89799 25449 106385 63405 76223 64616 27455 54740 78173 20193
## 1 1 3 3 1 1 1 3 2 2 1
## 66701 97201 22467 95362 63167 79225 63658 49862 84032 79331 84955
## 1 2 2 2 1 2 1 3 1 1 2
## 51491 15703 6623 8983 37769 29479 70943 98170 78121 86621 1835
## 2 2 3 1 1 2 2 1 1 1 1
## 42221 21099 41043 90978 56529 36940 105689 97455 76099 38265 76384
## 2 2 1 1 2 3 2 1 1 2 1
## 46438 75176 88461 69350 8176 94119 76369 17746 53873 29133 31
## 1 1 1 1 3 2 1 2 1 3 2
## 7588 4620 45980 68783 51573 89552 70778 11667 33027 87905 70945
## 3 2 2 1 2 1 1 3 2 1 2
## 91467 76792 89436 2450 44500 1673 19851 48434 83529 6007 83680
## 2 1 1 1 1 1 2 1 1 2 1
## 55992 90779 78967 104003 100264 66596 60906 78715 93289 46468 1204
## 2 1 1 2 2 1 1 2 1 1 1
## 97653 53272 24111 75455 43694 103727 3984 7880 57722 22119 67632
## 1 3 3 2 3 1 2 3 1 2 1
## 86409 52523 53918 24522 6333 68430 90232 89419 55737 19955 55368
## 1 3 2 2 2 1 2 1 1 2 1
## 47818 14417 49286 92916 25244 106545 5596 40276 60101 37167 69232
## 1 2 3 1 3 1 1 3 1 1 1
## 22974 52851 4913 10301 76908 99701 18547 104024 78774 29370 46843
## 2 2 2 1 1 1 2 2 1 1 1
## 58102 36086 76723 82171 107139 9182 103746 71848 88852 82585 56519
## 1 1 2 1 2 1 2 2 2 1 2
## 106941 24671 93648 34134 47800 25196 65778 7071 40160 1498 57337
## 1 3 1 3 1 3 1 3 3 1 1
## 60587 20698 65615 9723 104685 34599 4518 62170 81882 4695 32102
## 1 2 1 3 2 1 2 2 1 2 2
## 78889 81025 97142 74984 92556 53289 16436 26691 53705 42887 30237
## 1 2 2 3 1 3 2 1 2 3 1
## 66766 35556 32076 26715 18388 82526 23977 68616 63481 31315 43755
## 1 2 2 1 2 1 1 1 1 2 2
## 45555 57943 74659 73799 102346 20400 4972 69045 37492 6373 73396
## 3 1 2 2 2 3 2 1 3 1 3
## 82756 602 74059 47606 28577 7877 58263 2777 30712 17749 7488
## 1 1 1 2 2 3 1 3 1 2 3
## 101452 76662 100100 45430 106945 9739 61775 19512 80143 49588 101353
## 2 1 1 2 1 2 2 2 2 2 1
## 49753 90499 52292 101096 38245 99046 4682 68957 37765 34827 86479
## 3 2 2 1 2 2 1 1 1 2 1
## 2748 56138 44859 101888 51442 78912 104620 75936 57223 67089 97664
## 3 1 3 3 1 1 2 1 1 1 1
## 27365 76141 87938 19927 10216 2882 4015 27913 29465 9174 102856
## 3 2 1 1 1 1 1 1 1 2 2
## 7657 31351 68553 83192 42155 65995 92999 106635 10044 93926 14666
## 3 2 1 1 3 2 1 2 1 1 2
## 26226 54371 91194 72668 38920 96855 19360 94407 22344 98763 42039
## 3 1 1 1 2 1 2 1 1 1 3
## 83836 51953 91407 86414 95387 36385 101138 74075 101450 36671 29343
## 1 2 1 1 2 3 2 2 2 3 3
## 47159 34162 70508 66396 65053 100887 83653 81490 76877 24243 74441
## 1 2 1 1 2 3 1 1 1 1 1
## 36829 41218 67499 23294 76805 27103 83355 1923 31466 5178 8482
## 2 2 2 2 2 3 1 2 2 1 1
## 49618 106467 78638 47695 48775 100232 61449 43289 91176 81547 102798
## 2 1 1 3 2 3 1 1 1 1 1
## 12636 20547 69340 37247 37015 53719 37208 18876 17017 26566 62506
## 2 2 1 2 3 1 1 2 1 1 2
## 92120 106720 74640 39264 60225 89914 107815 13763 79126 15828 4750
## 2 3 1 2 1 1 3 3 1 1 2
## 18807 91870 107609 91570 41609 13797 56767 8848 38947 101914 50212
## 2 1 1 2 1 1 1 2 2 2 3
## 12791 7196 25245 58156 64797 75869 35533 65463 98821 52572 99750
## 2 3 2 1 1 1 2 2 1 3 1
## 2647 80352 34796 83727 38582 68362 85929 21086 94388 18304 2761
## 1 2 2 1 1 1 1 2 1 2 3
## 47651 99007 76 56753 16029 37853 40302 75133 4297 61429 63754
## 3 1 1 2 2 3 3 1 3 1 2
## 47529 37106 101880 40838 91239 55888 83618 101534 99285 34490 55582
## 2 2 2 2 1 3 1 1 3 3 2
## 19879 37294 31859 101916 74482 6529 89521 15524 7053 82255 2222
## 2 3 2 2 1 3 1 2 3 2 1
## 87671 88940 90727 97700 20995 40459 11166 35046 95455 16322 42611
## 2 1 1 1 2 3 2 3 2 1 2
## 39155 65854 1627 96703 53391 32035 75938 28613 19586 103912 11735
## 2 1 1 1 1 3 1 2 1 2 2
## 77589 105747 53971 40133 23248 4968 77872 56986 80931 44447 24728
## 1 2 3 3 2 2 2 1 1 1 2
## 52551 30541 15546 80653 98116 49689 62133 10550 86015 87576 103582
## 3 2 2 1 1 1 2 3 1 3 2
## 61118 72047 28535 19685 90544 56471 99374 40159 32661 49408 28999
## 2 2 2 2 2 1 2 3 2 1 3
## 17711 73171 47505 7789 12447 74556 95877 4298 25948 47534 65505
## 2 2 2 3 2 1 1 2 1 2 1
## 72884 68703 93017 756 13157 28676 64750 80650 102016 93955 104652
## 1 1 1 1 1 2 1 1 1 1 3
## 14600 27525 24934 78082 887 28360 914 92958 14405 45533 92684
## 2 2 3 2 1 2 1 1 2 2 1
## 81921 80734 96754 36234 83712 93439 63967 5799 91468 20874 84189
## 1 1 1 1 1 2 1 1 2 2 1
## 20474 14478 10943 1789 23506 93970 32638 5483 72383 41125 91154
## 2 2 2 1 3 1 2 3 2 2 1
## 22849 58127 38854 4961 77224 84796 73717 3004 8390 30774 47868
## 2 1 2 2 1 1 1 1 2 2 1
## 64790 91311 88178 15017 67101 50108 77784 33037 58460 82412 52243
## 1 1 1 3 2 1 2 2 1 2 2
## 54335 61595 72070 47332 25082 99710 58012 51396 2437 26219 91129
## 1 2 1 3 2 2 1 2 2 1 2
## 18771 102159 43025 41513 18671 100862 21556 2315 39113 70995 57334
## 2 3 3 2 2 2 1 1 3 2 1
## 55241 42775 77841 71112 104519 40332 4176 57247 61973 99134 72732
## 2 2 1 2 1 3 2 1 2 2 2
## 90266 20570 51114 78457 29278 39404 53042 352 65920 51260 24163
## 1 2 3 1 3 3 3 1 2 2 2
## 40818 32763 91819 61328 1191 98032 22660 59555 39396 95542 82243
## 2 1 1 2 1 1 2 1 3 2 1
## 30933 17832 40197 4588 89671 2304 21771 33442 68813 103715 99515
## 3 2 2 2 2 1 2 1 2 1 3
## 39150 45174 30536 29444 65839 92174 56987 57777 57766 32817 79173
## 3 2 1 2 1 1 1 1 1 2 3
## 20696 86160 51051 31566 50878 1003 80926 84909 70212 37984 87509
## 2 1 3 2 2 1 2 1 1 1 1
## 56785 14632 58085 53547 24226 9008 88320 74884 81626 51417 25681
## 1 2 1 2 2 1 1 1 2 1 2
## 39460 64935 48187 36573 54047 100649 17955 57137 36091 40269 102575
## 3 1 3 3 1 1 2 2 3 3 2
## 41194 5392 45030 9563 97416 32710 24790 70405 28650 2473 76085
## 3 1 2 2 1 1 2 1 2 1 2
## 52818 18937 43801 82422 50036 83098 31072 50814 10174 16021 13939
## 3 2 1 1 1 1 2 3 1 2 2
## 89105 68446 102808 57539 35544 42459 86615 12334 30092 13448 9046
## 1 1 1 1 2 2 1 2 3 3 3
## 95109 81997 10847 75796 58552 94933 9471 33714 105929 3649 80075
## 2 2 3 2 3 2 2 1 1 1 1
## 17521 105422 12530 15886 65768 94245 12893 81969 103367 37856 14610
## 3 1 2 2 2 1 2 1 1 3 2
## 48268 62339 48814 76991 78628 31389 107789 76202 73910 55791 54816
## 2 2 1 1 1 2 2 2 1 1 3
## 674 17674 61189 59857 26234 25855 68747 7103 86201 85279 1762
## 2 1 2 1 3 3 1 3 1 1 1
## 27251 69961 88698 63162 13344 83956 97921 79943 1607 43391 14303
## 1 1 2 1 3 1 1 1 1 3 2
## 67147 99873 61034 90361 9813 102375 99314 77391 68807 72042 90928
## 2 2 2 1 1 1 2 2 1 2 1
## 46339 10557 19807 91903 73691 46129 65308 28623 94953 27955 3302
## 3 2 2 1 1 3 1 2 2 1 3
## 55209 51897 96062 1847 11276 60972 104292 8412 46971 66737 104770
## 1 1 2 1 2 3 3 2 3 1 2
## 46355 18535 7111 72300 41939 85560 106988 3366 66984 87078 12083
## 2 2 3 3 3 1 2 3 1 1 2
## 56286 42481 96085 81623 42868 63521 51186 18970 64687 49957 81019
## 2 3 1 3 2 2 1 2 1 2 1
## 22312 64353 73796 66844 82487 20439 67538 29708 3288 98520 11159
## 3 1 2 1 2 2 2 3 2 1 2
## 72778 101252 27644 81147 57436 40703 12467 86872 65864 43474 38461
## 1 2 1 1 1 2 2 1 1 3 2
## 34622 45776 15127 5190 101849 13835 46988 4798 60389 10247 70345
## 3 2 2 2 3 1 2 3 2 1 1
## 23948 95993 53980 47840 4343 81107 27682 46776 58700 82762 43536
## 1 1 1 2 2 1 1 3 2 1 1
## 102986 26818 30856 16225 30552 528 90279 74686 663 96403 65228
## 3 1 2 3 2 1 1 1 2 2 2
## 101266 59056 105495 60043 86011 30481 66329 107917 28476 22232
## 1 1 2 2 1 2 1 2 2 1fcm_res$centers## PM2.5 PM10 NO NO2 NOx NH3
## 1 -0.42688785 -0.39849245 -0.34463029 -0.392531445 -0.36695628 -0.2344292
## 2 -0.01677294 -0.01535908 -0.06614412 -0.006638347 -0.06941096 -0.0129972
## 3 1.21842644 1.16368550 1.16182025 1.014801479 1.20587769 0.6198301
## CO SO2 O3 Benzene Toluene Xylene
## 1 -0.12719077 -0.194219091 -0.07501770 -0.18290465 -0.20918853 -0.085969234
## 2 -0.03907261 0.001858873 0.03517847 -0.02168255 -0.03635418 -0.002085232
## 3 0.30393242 0.346965935 -0.05612896 0.49149758 0.58922724 0.187923620
## AQI
## 1 -0.51487191
## 2 0.01804683
## 3 1.26424424fcm_res$membership## 1 2 3
## 51663 0.01238009 0.9859554 0.001664465
## 57870 0.65384966 0.2879619 0.058188489
## 2986 0.60636712 0.3287348 0.064898076
## 29925 0.42836908 0.4391820 0.132448873
## 95246 0.11197491 0.8727289 0.015296225
## 103065 0.32529466 0.3343285 0.340376819
## 68293 0.01238009 0.9859554 0.001664465
## 62555 0.71108309 0.2543018 0.034615136
## 45404 0.49040740 0.4584658 0.051126819
## 65161 0.55140634 0.3847708 0.063822871
## 46435 0.71739709 0.2529269 0.029676042
## 104474 0.34108998 0.5946465 0.064263523
## 9642 0.61326759 0.3586307 0.028101716
## 59134 0.59821668 0.3246570 0.077126356
## 52132 0.01238009 0.9859554 0.001664465
## 96849 0.69536698 0.2597494 0.044883598
## 14183 0.01238009 0.9859554 0.001664465
## 15180 0.57136538 0.3587748 0.069859860
## 27168 0.28669545 0.4581322 0.255172316
## 89709 0.52597092 0.4129495 0.061079531
## 9097 0.29070978 0.5850753 0.124214974
## 30538 0.44694724 0.4532219 0.099830885
## 56219 0.01238009 0.9859554 0.001664465
## 94517 0.45488163 0.4618324 0.083286011
## 7989 0.27461235 0.4876377 0.237749943
## 13536 0.56318500 0.3667012 0.070113763
## 90077 0.26568345 0.3240395 0.410277083
## 6216 0.54880465 0.3625240 0.088671371
## 83519 0.53844848 0.3822484 0.079303088
## 29394 0.29515635 0.5352460 0.169597622
## 53241 0.52398200 0.4000635 0.075954509
## 28825 0.45098032 0.4939590 0.055060660
## 106773 0.38705341 0.4976656 0.115280988
## 41 0.45066955 0.4445843 0.104746162
## 14426 0.01238009 0.9859554 0.001664465
## 105695 0.33081738 0.5361231 0.133059526
## 72820 0.59842801 0.3286461 0.072925910
## 51656 0.01238009 0.9859554 0.001664465
## 94038 0.58278614 0.3360466 0.081167300
## 58527 0.56133180 0.3776652 0.061003038
## 77009 0.59155721 0.3187563 0.089686471
## 43042 0.17887477 0.2301958 0.590929408
## 77837 0.43409697 0.4845653 0.081337744
## 6134 0.43791494 0.4286896 0.133395407
## 33523 0.19667215 0.2687421 0.534585781
## 21812 0.33697509 0.6319445 0.031080427
## 39895 0.73410659 0.2446918 0.021201627
## 9640 0.64381169 0.3116201 0.044568228
## 85278 0.60104223 0.3122200 0.086737775
## 9326 0.11184532 0.8730080 0.015146721
## 26510 0.27372555 0.3017567 0.424517743
## 20960 0.11197491 0.8727289 0.015296225
## 14403 0.01238009 0.9859554 0.001664465
## 64502 0.64753172 0.2879213 0.064546974
## 71503 0.11197491 0.8727289 0.015296225
## 45221 0.45098032 0.4939590 0.055060660
## 94335 0.46111074 0.4076440 0.131245214
## 92372 0.48726809 0.4653913 0.047340645
## 77585 0.56424199 0.3956195 0.040138547
## 80686 0.46952308 0.4316791 0.098797848
## 70563 0.57900475 0.3316993 0.089295975
## 32606 0.51763958 0.4158436 0.066516845
## 16152 0.46189558 0.4707008 0.067403605
## 25559 0.11908024 0.1744412 0.706478586
## 14215 0.01238009 0.9859554 0.001664465
## 14287 0.01238009 0.9859554 0.001664465
## 23194 0.39685850 0.5632398 0.039901676
## 90094 0.60321846 0.3435694 0.053212132
## 34976 0.50776331 0.4585911 0.033645567
## 14491 0.01238009 0.9859554 0.001664465
## 82949 0.69378786 0.2563025 0.049909629
## 77584 0.47004692 0.4863746 0.043578488
## 40503 0.18117292 0.2272884 0.591538721
## 34724 0.17070735 0.2454258 0.583866863
## 103662 0.67387771 0.2804500 0.045672311
## 86013 0.59353688 0.3274975 0.078965658
## 17369 0.63788918 0.2929193 0.069191497
## 31542 0.07570732 0.9147786 0.009514065
## 102537 0.17680267 0.2612515 0.561945813
## 59106 0.64713251 0.2973163 0.055551171
## 86605 0.54896122 0.3838890 0.067149778
## 40632 0.53698295 0.3797413 0.083275761
## 96111 0.37320883 0.3909666 0.235824584
## 43204 0.23305588 0.4323007 0.334643409
## 37544 0.35629955 0.5154363 0.128264127
## 99289 0.39591729 0.5419812 0.062101554
## 84427 0.41776553 0.3996270 0.182607495
## 76820 0.58789529 0.3640842 0.048020542
## 82115 0.56624174 0.4011443 0.032613963
## 44196 0.59489455 0.3309997 0.074105713
## 92337 0.51407493 0.4191004 0.066824647
## 44983 0.26586598 0.7098222 0.024311841
## 91438 0.31786153 0.4229829 0.259155558
## 36717 0.73495372 0.2477686 0.017277634
## 28078 0.42578980 0.4038407 0.170369502
## 69369 0.58649660 0.3340509 0.079452457
## 91564 0.01238009 0.9859554 0.001664465
## 43406 0.22178441 0.2904598 0.487755805
## 41488 0.36084285 0.4797313 0.159425826
## 47485 0.24511038 0.3828684 0.372021260
## 63528 0.59588875 0.3362170 0.067894270
## 14536 0.01238009 0.9859554 0.001664465
## 83069 0.29768818 0.3478697 0.354442145
## 51465 0.58972722 0.3301484 0.080124368
## 26503 0.25486235 0.3695802 0.375557416
## 103319 0.45632541 0.4317256 0.111949029
## 88299 0.46352760 0.4765217 0.059950745
## 32953 0.13188364 0.2249985 0.643117865
## 413 0.28741667 0.3673283 0.345255068
## 10762 0.34252049 0.3688594 0.288620098
## 48182 0.16082564 0.2095341 0.629640257
## 30571 0.30336004 0.5020399 0.194600035
## 42521 0.27142989 0.3705629 0.358007227
## 74522 0.72988203 0.2316526 0.038465388
## 14745 0.34772614 0.6106338 0.041640028
## 25946 0.34380568 0.5440918 0.112102509
## 80340 0.42467230 0.4805773 0.094750374
## 43928 0.14266131 0.1982518 0.659086921
## 6601 0.21977761 0.2832378 0.496984600
## 57701 0.67932567 0.2792512 0.041423118
## 53518 0.01238009 0.9859554 0.001664465
## 72326 0.37687894 0.4757259 0.147395140
## 52353 0.30257773 0.3339644 0.363457869
## 66154 0.68950412 0.2658194 0.044676468
## 47802 0.68776422 0.2763545 0.035881308
## 31517 0.01061084 0.9879975 0.001391709
## 66075 0.48040237 0.4095329 0.110064763
## 32263 0.35138908 0.4953610 0.153249953
## 95989 0.35857036 0.6049161 0.036513549
## 69161 0.67114265 0.2704547 0.058402640
## 81118 0.64084455 0.3207274 0.038428097
## 56157 0.47973517 0.4685166 0.051748243
## 19392 0.24788171 0.5236845 0.228433815
## 46137 0.25435419 0.4781693 0.267476497
## 67747 0.37180096 0.5828934 0.045305611
## 2286 0.65198050 0.2966923 0.051327226
## 59970 0.65494215 0.3079515 0.037106318
## 84298 0.65619697 0.2873427 0.056460301
## 54661 0.57287839 0.3639325 0.063189061
## 32281 0.68965458 0.2715119 0.038833498
## 107575 0.72381719 0.2421251 0.034057692
## 64085 0.01238009 0.9859554 0.001664465
## 7826 0.23433568 0.2738438 0.491820502
## 80287 0.49577330 0.4289952 0.075231529
## 89799 0.54368468 0.4139509 0.042364387
## 25449 0.22639091 0.2667012 0.506907913
## 106385 0.20395137 0.2771267 0.518921913
## 63405 0.57543335 0.3458730 0.078693669
## 76223 0.46497605 0.4079678 0.127056097
## 64616 0.59379105 0.3388182 0.067390724
## 27455 0.10448091 0.1604509 0.735068233
## 54740 0.28294086 0.5423492 0.174709968
## 78173 0.35977169 0.4162205 0.224007839
## 20193 0.67745047 0.2780451 0.044504403
## 66701 0.69754936 0.2618520 0.040598676
## 97201 0.33186606 0.6235670 0.044566943
## 22467 0.32656808 0.3980345 0.275397389
## 95362 0.11197491 0.8727289 0.015296225
## 63167 0.67249746 0.2838281 0.043674399
## 79225 0.31080182 0.3451708 0.344027352
## 63658 0.67049418 0.2775717 0.051934133
## 49862 0.15392636 0.2207243 0.625349388
## 84032 0.57796377 0.3574205 0.064615739
## 79331 0.62653131 0.3212788 0.052189870
## 84955 0.41729678 0.4188170 0.163886195
## 51491 0.35300139 0.3745545 0.272444143
## 15703 0.22655189 0.4487000 0.324748063
## 6623 0.23531431 0.2967893 0.467896432
## 8983 0.73890929 0.2295860 0.031504660
## 37769 0.67968832 0.2816071 0.038704577
## 29479 0.34158416 0.5248609 0.133554952
## 70943 0.44741203 0.4712044 0.081383542
## 98170 0.67378279 0.2740676 0.052149612
## 78121 0.46427016 0.3996697 0.136060092
## 86621 0.63642714 0.3078899 0.055683012
## 1835 0.49521391 0.4198098 0.084976284
## 42221 0.38861125 0.4446691 0.166719672
## 21099 0.11197491 0.8727289 0.015296225
## 41043 0.53957056 0.3814377 0.078991736
## 90978 0.50242712 0.4130522 0.084520641
## 56529 0.01238009 0.9859554 0.001664465
## 36940 0.16994071 0.2268903 0.603169000
## 105689 0.34545704 0.4890083 0.165534648
## 97455 0.67943428 0.2737525 0.046813205
## 76099 0.41487564 0.3831179 0.202006417
## 38265 0.01238009 0.9859554 0.001664465
## 76384 0.59846994 0.3334837 0.068046405
## 46438 0.51039679 0.4424164 0.047186825
## 75176 0.61017750 0.3086731 0.081149400
## 88461 0.44569265 0.4355246 0.118782759
## 69350 0.59230302 0.3187587 0.088938259
## 8176 0.20086749 0.2473398 0.551792732
## 94119 0.35605235 0.4650941 0.178853563
## 76369 0.61756197 0.3016119 0.080826139
## 17746 0.01238009 0.9859554 0.001664465
## 53873 0.73453333 0.2319609 0.033505770
## 29133 0.26459150 0.3426667 0.392741810
## 31 0.36412535 0.5116989 0.124175752
## 7588 0.18712525 0.2400546 0.572820154
## 4620 0.38725792 0.4035811 0.209161026
## 45980 0.25973641 0.5641936 0.176070000
## 68783 0.74578070 0.2197658 0.034453469
## 51573 0.01238009 0.9859554 0.001664465
## 89552 0.59231798 0.3344864 0.073195665
## 70778 0.62929558 0.2978144 0.072890011
## 11667 0.25755645 0.2910788 0.451364742
## 33027 0.46123610 0.4765946 0.062169340
## 87905 0.57828446 0.3225672 0.099148346
## 70945 0.43252033 0.4862128 0.081266870
## 91467 0.39651464 0.4545518 0.148933571
## 76792 0.65049410 0.3059875 0.043518400
## 89436 0.61718177 0.3226554 0.060162866
## 2450 0.49936425 0.4268434 0.073792377
## 44500 0.45540916 0.4429460 0.101644803
## 1673 0.64603209 0.3030875 0.050880418
## 19851 0.31715883 0.4505676 0.232273569
## 48434 0.61094821 0.3290310 0.060020763
## 83529 0.55061572 0.3844056 0.064978702
## 6007 0.32589335 0.4948155 0.179291203
## 83680 0.63747977 0.3068910 0.055629198
## 55992 0.34534852 0.5569881 0.097663352
## 90779 0.46108750 0.4534242 0.085488337
## 78967 0.71789339 0.2516623 0.030444355
## 104003 0.35137808 0.5370240 0.111597952
## 100264 0.28528060 0.4442250 0.270494431
## 66596 0.69190831 0.2762429 0.031848759
## 60906 0.65629496 0.2863687 0.057336317
## 78715 0.29842188 0.5074415 0.194136586
## 93289 0.48397923 0.4544095 0.061611246
## 46468 0.60737090 0.3471141 0.045514972
## 1204 0.63430797 0.2996739 0.066018131
## 97653 0.60157865 0.3563348 0.042086499
## 53272 0.19728658 0.2663258 0.536387654
## 24111 0.19895557 0.2505864 0.550458062
## 75455 0.37911060 0.4796151 0.141274255
## 43694 0.18590979 0.2838180 0.530272257
## 103727 0.70265677 0.2555652 0.041778075
## 3984 0.01238009 0.9859554 0.001664465
## 7880 0.20736833 0.2510939 0.541537780
## 57722 0.63396145 0.3193552 0.046683378
## 22119 0.25514496 0.6007998 0.144055221
## 67632 0.63617447 0.3139220 0.049903528
## 86409 0.60026824 0.3607790 0.038952714
## 52523 0.30616616 0.3340218 0.359812037
## 53918 0.32380695 0.6142217 0.061971303
## 24522 0.36594318 0.5745255 0.059531297
## 6333 0.36117015 0.4958929 0.142936953
## 68430 0.68531258 0.2736522 0.041035249
## 90232 0.01238009 0.9859554 0.001664465
## 89419 0.59182956 0.3491981 0.058972386
## 55737 0.68637162 0.2680309 0.045597524
## 19955 0.37961579 0.4418829 0.178501338
## 55368 0.73863144 0.2365437 0.024824843
## 47818 0.71882323 0.2429023 0.038274451
## 14417 0.01238009 0.9859554 0.001664465
## 49286 0.10754330 0.1711975 0.721259181
## 92916 0.50985062 0.4196640 0.070485351
## 25244 0.22717632 0.3455516 0.427272110
## 106545 0.66652154 0.2798439 0.053634538
## 5596 0.35058880 0.3467820 0.302629225
## 40276 0.16281319 0.2350426 0.602144190
## 60101 0.43263609 0.4126439 0.154719970
## 37167 0.40987136 0.4091209 0.181007690
## 69232 0.63084315 0.2942316 0.074925218
## 22974 0.32365948 0.6219384 0.054402103
## 52851 0.45618957 0.4591860 0.084624411
## 4913 0.36998778 0.5453415 0.084670738
## 10301 0.73899967 0.2431807 0.017819593
## 76908 0.67077560 0.2798326 0.049391763
## 99701 0.59412425 0.3455953 0.060280445
## 18547 0.17015729 0.7958259 0.034016857
## 104024 0.23466673 0.4078177 0.357515546
## 78774 0.58888880 0.3201293 0.090981940
## 29370 0.51984359 0.4184465 0.061709920
## 46843 0.49550918 0.4637392 0.040751637
## 58102 0.72144221 0.2450306 0.033527192
## 36086 0.49876630 0.4003644 0.100869264
## 76723 0.33627162 0.4548261 0.208902273
## 82171 0.72846378 0.2425962 0.028940010
## 107139 0.43936447 0.5213046 0.039330913
## 9182 0.59940551 0.3711873 0.029407222
## 103746 0.01238009 0.9859554 0.001664465
## 71848 0.41133012 0.5018558 0.086814050
## 88852 0.01238009 0.9859554 0.001664465
## 82585 0.62502121 0.3353329 0.039645928
## 56519 0.33296545 0.3446114 0.322423171
## 106941 0.57503496 0.3369852 0.087979802
## 24671 0.11908411 0.1667053 0.714210588
## 93648 0.69302060 0.2640615 0.042917886
## 34134 0.24108932 0.3771294 0.381781274
## 47800 0.60756826 0.3375850 0.054846704
## 25196 0.14990933 0.2140228 0.636067908
## 65778 0.68880754 0.2741079 0.037084554
## 7071 0.27002149 0.3008768 0.429101682
## 40160 0.20935588 0.2520246 0.538619556
## 1498 0.49099057 0.4402737 0.068735748
## 57337 0.61799349 0.3325763 0.049430182
## 60587 0.62914388 0.2963051 0.074551041
## 20698 0.28362818 0.4247367 0.291635168
## 65615 0.68374301 0.2782031 0.038053858
## 9723 0.12298827 0.1998552 0.677156532
## 104685 0.27880169 0.3847440 0.336454339
## 34599 0.63253890 0.3185014 0.048959662
## 4518 0.30600838 0.3723624 0.321629254
## 62170 0.25976818 0.6857451 0.054486753
## 81882 0.76587552 0.2057158 0.028408645
## 4695 0.34877657 0.4095306 0.241692819
## 32102 0.30013657 0.5074765 0.192386905
## 78889 0.44921970 0.4082506 0.142529718
## 81025 0.43819333 0.4534697 0.108336985
## 97142 0.33186606 0.6235670 0.044566943
## 74984 0.22809607 0.3490410 0.422862924
## 92556 0.63816017 0.3034843 0.058355505
## 53289 0.20636807 0.3521941 0.441437805
## 16436 0.43032830 0.5205816 0.049090051
## 26691 0.49623142 0.4089063 0.094862267
## 53705 0.42360103 0.4868736 0.089525383
## 42887 0.25818746 0.2950401 0.446772418
## 30237 0.44435294 0.4258297 0.129817382
## 66766 0.65327781 0.2880623 0.058659864
## 35556 0.36992008 0.4568774 0.173202495
## 32076 0.28886904 0.4960919 0.215039021
## 26715 0.51307454 0.4156496 0.071275852
## 18388 0.26723043 0.5934349 0.139334691
## 82526 0.65676258 0.2929581 0.050279354
## 23977 0.66565973 0.2840904 0.050249913
## 68616 0.48137471 0.4312630 0.087362319
## 63481 0.66579283 0.2854229 0.048784293
## 31315 0.22555639 0.4148305 0.359613068
## 43755 0.31347735 0.4048721 0.281650537
## 45555 0.17513684 0.2591860 0.565677117
## 57943 0.69605738 0.2601488 0.043793836
## 74659 0.40561299 0.5117990 0.082588007
## 73799 0.30836434 0.4599694 0.231666283
## 102346 0.37573941 0.5816892 0.042571383
## 20400 0.30127132 0.3492898 0.349438844
## 4972 0.01238009 0.9859554 0.001664465
## 69045 0.67395980 0.2721709 0.053869268
## 37492 0.17842641 0.2458852 0.575688418
## 6373 0.49314137 0.4340093 0.072849308
## 73396 0.24616697 0.3188535 0.434979490
## 82756 0.63570976 0.3241803 0.040109920
## 602 0.61371715 0.3088611 0.077421732
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## 39404 0.31209861 0.3285999 0.359301476
## 53042 0.31356642 0.3293815 0.357052083
## 352 0.45326660 0.4173353 0.129398142
## 65920 0.01238009 0.9859554 0.001664465
## 51260 0.34482842 0.3769271 0.278244477
## 24163 0.23556395 0.3849297 0.379506346
## 40818 0.30526462 0.4136955 0.281039881
## 32763 0.57406770 0.3437516 0.082180662
## 91819 0.49263258 0.4073021 0.100065344
## 61328 0.29571662 0.3525154 0.351768003
## 1191 0.65567214 0.3025994 0.041728413
## 98032 0.55035154 0.4040227 0.045625797
## 22660 0.01238009 0.9859554 0.001664465
## 59555 0.60139705 0.3356551 0.062947885
## 39396 0.28897081 0.3188571 0.392172059
## 95542 0.37414215 0.5659428 0.059915071
## 82243 0.75686440 0.2104555 0.032680151
## 30933 0.17090980 0.2315409 0.597549292
## 17832 0.30156426 0.6584959 0.039939810
## 40197 0.33857895 0.5123983 0.149022746
## 4588 0.35872606 0.4074503 0.233823616
## 89671 0.40128741 0.5028814 0.095831150
## 2304 0.67329619 0.2745750 0.052128841
## 21771 0.26665882 0.4353023 0.298038917
## 33442 0.46577709 0.3804020 0.153820880
## 68813 0.35380352 0.4552539 0.190942541
## 103715 0.68338628 0.2708966 0.045717101
## 99515 0.20309613 0.2956878 0.501216097
## 39150 0.31036163 0.3426873 0.346951113
## 45174 0.26512462 0.7077521 0.027123252
## 30536 0.64346321 0.3092153 0.047321507
## 29444 0.25146462 0.4104245 0.338110898
## 65839 0.70123432 0.2680115 0.030754162
## 92174 0.52255909 0.4397893 0.037651571
## 56987 0.59697417 0.3207981 0.082227687
## 57777 0.70535665 0.2571603 0.037483028
## 57766 0.65979068 0.2998735 0.040335809
## 32817 0.33668002 0.3419520 0.321367958
## 79173 0.32563271 0.3353584 0.339008887
## 20696 0.01238009 0.9859554 0.001664465
## 86160 0.60595718 0.3122043 0.081838538
## 51051 0.20358082 0.2490821 0.547337055
## 31566 0.13089879 0.8523342 0.016767052
## 50878 0.42156653 0.4722125 0.106221010
## 1003 0.47514364 0.4224344 0.102422005
## 80926 0.33660609 0.5358948 0.127499109
## 84909 0.63442304 0.2930874 0.072489537
## 70212 0.60621263 0.3120372 0.081750160
## 37984 0.65281562 0.2950644 0.052119992
## 87509 0.36424631 0.3637862 0.271967480
## 56785 0.63179936 0.3100008 0.058199878
## 14632 0.34772614 0.6106338 0.041640028
## 58085 0.70904701 0.2512596 0.039693431
## 53547 0.27232514 0.5207887 0.206886185
## 24226 0.28899074 0.4850650 0.225944231
## 9008 0.67851848 0.2738785 0.047603065
## 88320 0.57408063 0.3710111 0.054908261
## 74884 0.50285295 0.3834000 0.113747059
## 81626 0.29904333 0.4615206 0.239436078
## 51417 0.47937653 0.3997378 0.120885623
## 25681 0.31416273 0.5290946 0.156742632
## 39460 0.28988177 0.3184612 0.391656988
## 64935 0.57409123 0.3470695 0.078839301
## 48187 0.11533294 0.1627876 0.721879474
## 36573 0.19521637 0.2462320 0.558551671
## 54047 0.50574461 0.4156507 0.078604689
## 100649 0.59153065 0.3543994 0.054069924
## 17955 0.30156426 0.6584959 0.039939810
## 57137 0.38135756 0.4444073 0.174235135
## 36091 0.19246807 0.2654136 0.542118356
## 40269 0.16367249 0.2566120 0.579715485
## 102575 0.24571681 0.3879539 0.366329245
## 41194 0.22092630 0.3314510 0.447622747
## 5392 0.61314545 0.3073375 0.079517004
## 45030 0.38864706 0.5799798 0.031373160
## 9563 0.41715168 0.5262457 0.056602611
## 97416 0.63826552 0.2996605 0.062074023
## 32710 0.46983912 0.4227369 0.107424019
## 24790 0.31256537 0.5502504 0.137184229
## 70405 0.61672839 0.3089088 0.074362780
## 28650 0.45098032 0.4939590 0.055060660
## 2473 0.66604426 0.2844619 0.049493843
## 76085 0.42348587 0.4336978 0.142816328
## 52818 0.31641140 0.3298570 0.353731621
## 18937 0.28941988 0.6499121 0.060668045
## 43801 0.48377646 0.3951545 0.121068997
## 82422 0.46156437 0.4512845 0.087151112
## 50036 0.55221224 0.3636988 0.084088924
## 83098 0.56973741 0.3799122 0.050350415
## 31072 0.34821381 0.5426638 0.109122368
## 50814 0.23446349 0.3385995 0.426937035
## 10174 0.54533789 0.4030150 0.051647144
## 16021 0.40084479 0.4402310 0.158924170
## 13939 0.01238009 0.9859554 0.001664465
## 89105 0.46108750 0.4534242 0.085488337
## 68446 0.62397025 0.3110418 0.064987912
## 102808 0.68962584 0.2654542 0.044919927
## 57539 0.65481718 0.2904503 0.054732478
## 35544 0.30391033 0.3555470 0.340542633
## 42459 0.01238009 0.9859554 0.001664465
## 86615 0.56671835 0.3974275 0.035854185
## 12334 0.01238009 0.9859554 0.001664465
## 30092 0.21701296 0.2647237 0.518263359
## 13448 0.29077239 0.3199144 0.389313186
## 9046 0.13829208 0.1925595 0.669148400
## 95109 0.11197491 0.8727289 0.015296225
## 81997 0.26440885 0.5442744 0.191316726
## 10847 0.26851628 0.3099953 0.421488380
## 75796 0.26152766 0.5989051 0.139567196
## 58552 0.27356668 0.3218605 0.404572791
## 94933 0.35329203 0.3602108 0.286497182
## 9471 0.31849568 0.6443528 0.037151566
## 33714 0.39319139 0.3711278 0.235680779
## 105929 0.38680412 0.3646956 0.248500237
## 3649 0.50169458 0.3919915 0.106313942
## 80075 0.43771747 0.3860189 0.176263639
## 17521 0.12723017 0.2160168 0.656752985
## 105422 0.61988197 0.3042304 0.075887586
## 12530 0.01238009 0.9859554 0.001664465
## 15886 0.40303313 0.4630445 0.133922346
## 65768 0.33417009 0.3390166 0.326813340
## 94245 0.67254936 0.2716754 0.055775217
## 12893 0.01238009 0.9859554 0.001664465
## 81969 0.71925120 0.2383405 0.042408320
## 103367 0.65168347 0.2957529 0.052563621
## 37856 0.17834886 0.2480833 0.573567793
## 14610 0.34772614 0.6106338 0.041640028
## 48268 0.22297313 0.7128837 0.064143212
## 62339 0.07915918 0.9128301 0.008010758
## 48814 0.53824454 0.3604428 0.101312684
## 76991 0.52680744 0.3534747 0.119717911
## 78628 0.60203105 0.3174160 0.080552987
## 31389 0.30779272 0.6079504 0.084256926
## 107789 0.34729921 0.5225331 0.130167658
## 76202 0.37026798 0.5255045 0.104227520
## 73910 0.58117003 0.3340891 0.084740876
## 55791 0.60589739 0.3297376 0.064365045
## 54816 0.29655321 0.3261102 0.377336573
## 674 0.01238009 0.9859554 0.001664465
## 17674 0.58464738 0.3601705 0.055182132
## 61189 0.01238009 0.9859554 0.001664465
## 59857 0.51458892 0.4171334 0.068277636
## 26234 0.28695636 0.3495904 0.363453255
## 25855 0.16435660 0.2131427 0.622500728
## 68747 0.60374732 0.3365592 0.059693486
## 7103 0.23851860 0.2841202 0.477361178
## 86201 0.62870660 0.3044646 0.066828815
## 85279 0.59690333 0.3138754 0.089221220
## 1762 0.48893842 0.4162514 0.094810218
## 27251 0.69506473 0.2602888 0.044646457
## 69961 0.62428676 0.3160114 0.059701814
## 88698 0.36921215 0.4562014 0.174586459
## 63162 0.65876359 0.2969985 0.044237954
## 13344 0.20206376 0.2518028 0.546133412
## 83956 0.60471525 0.3277374 0.067547391
## 97921 0.68928820 0.2645071 0.046204717
## 79943 0.65696012 0.2875131 0.055526814
## 1607 0.51449340 0.3871859 0.098320722
## 43391 0.21544071 0.2887677 0.495791631
## 14303 0.01238009 0.9859554 0.001664465
## 67147 0.37180096 0.5828934 0.045305611
## 99873 0.24281215 0.4693416 0.287846244
## 61034 0.01238009 0.9859554 0.001664465
## 90361 0.61918536 0.3233599 0.057454792
## 9813 0.63731032 0.3367185 0.025971202
## 102375 0.57376491 0.3846872 0.041547931
## 99314 0.01238009 0.9859554 0.001664465
## 77391 0.36905267 0.4808867 0.150060600
## 68807 0.49475454 0.4280797 0.077165716
## 72042 0.39261418 0.5290069 0.078378949
## 90928 0.46108750 0.4534242 0.085488337
## 46339 0.10330836 0.1623429 0.734348750
## 10557 0.32676773 0.3639710 0.309261277
## 19807 0.21211598 0.4600826 0.327801404
## 91903 0.63981390 0.3053997 0.054786436
## 73691 0.64647084 0.2856802 0.067848994
## 46129 0.21957250 0.3358713 0.444556223
## 65308 0.73840673 0.2309866 0.030606663
## 28623 0.01238009 0.9859554 0.001664465
## 94953 0.36124923 0.3648776 0.273873158
## 27955 0.52384511 0.3981239 0.078031018
## 3302 0.24732246 0.2925965 0.460081038
## 55209 0.53309009 0.4241113 0.042798575
## 51897 0.40828587 0.3986502 0.193063949
## 96062 0.39100662 0.4660011 0.142992271
## 1847 0.46626907 0.4367465 0.096984454
## 11276 0.32371553 0.5799059 0.096378582
## 60972 0.26587827 0.3444241 0.389697649
## 104292 0.16201014 0.2595909 0.578398931
## 8412 0.35619526 0.3817551 0.262049642
## 46971 0.27019017 0.3605890 0.369220801
## 66737 0.65431243 0.2874817 0.058205870
## 104770 0.47054308 0.4893954 0.040061535
## 46355 0.24603381 0.4023084 0.351657802
## 18535 0.29850561 0.6427811 0.058713244
## 7111 0.20907182 0.2539805 0.536947702
## 72300 0.19255594 0.2997790 0.507665079
## 41939 0.17240309 0.2283217 0.599275200
## 85560 0.60711210 0.3097115 0.083176423
## 106988 0.36413513 0.4503231 0.185541730
## 3366 0.20177910 0.2641562 0.534064667
## 66984 0.66977061 0.2871932 0.043036152
## 87078 0.50495706 0.3873803 0.107662649
## 12083 0.01238009 0.9859554 0.001664465
## 56286 0.01238009 0.9859554 0.001664465
## 42481 0.23624547 0.2891339 0.474620621
## 96085 0.64096299 0.3071665 0.051870510
## 81623 0.22624838 0.2894312 0.484320449
## 42868 0.28609834 0.4992933 0.214608346
## 63521 0.46137601 0.4646380 0.073985988
## 51186 0.79191894 0.1872122 0.020868821
## 18970 0.29012615 0.6151603 0.094713597
## 64687 0.53969336 0.3965773 0.063729364
## 49957 0.27390638 0.4074884 0.318605246
## 81019 0.64902705 0.2993893 0.051583626
## 22312 0.26078588 0.3557397 0.383474443
## 64353 0.56536736 0.3648847 0.069747965
## 73796 0.33507625 0.4698170 0.195106794
## 66844 0.62459028 0.3205240 0.054885683
## 82487 0.37426149 0.5389001 0.086838361
## 20439 0.01238009 0.9859554 0.001664465
## 67538 0.37180096 0.5828934 0.045305611
## 29708 0.13798671 0.1998714 0.662141894
## 3288 0.37279411 0.4525574 0.174648452
## 98520 0.63572713 0.2949754 0.069297466
## 11159 0.01238009 0.9859554 0.001664465
## 72778 0.47727919 0.4105856 0.112135205
## 101252 0.38941234 0.4685995 0.141988154
## 27644 0.64277990 0.2961591 0.061061028
## 81147 0.59555215 0.3184158 0.086032003
## 57436 0.67657989 0.2757239 0.047696215
## 40703 0.40526533 0.4867564 0.107978258
## 12467 0.01238009 0.9859554 0.001664465
## 86872 0.46514743 0.4158915 0.118961052
## 65864 0.72286730 0.2442111 0.032921614
## 43474 0.20561426 0.3670075 0.427378242
## 38461 0.31765306 0.3598735 0.322473476
## 34622 0.20705744 0.3023158 0.490626734
## 45776 0.20820479 0.4446875 0.347107740
## 15127 0.32624748 0.3975520 0.276200550
## 5190 0.38442984 0.4210736 0.194496554
## 101849 0.24813773 0.3588021 0.393060175
## 13835 0.70653469 0.2549167 0.038548649
## 46988 0.27067736 0.4652365 0.264086136
## 4798 0.21300954 0.2835349 0.503455568
## 60389 0.45695657 0.4915657 0.051477764
## 10247 0.72579108 0.2514189 0.022790032
## 70345 0.57617796 0.3384645 0.085357535
## 23948 0.62636883 0.3282201 0.045411089
## 95993 0.48722988 0.4368874 0.075882723
## 53980 0.73306550 0.2391460 0.027788514
## 47840 0.39519592 0.4239202 0.180883875
## 4343 0.32331953 0.3415524 0.335128068
## 81107 0.64707112 0.3008469 0.052081939
## 27682 0.68150939 0.2652777 0.053212865
## 46776 0.27075143 0.3404115 0.388837028
## 58700 0.01238009 0.9859554 0.001664465
## 82762 0.64365330 0.3197576 0.036589111
## 43536 0.57591489 0.3452121 0.078873046
## 102986 0.31801331 0.3305716 0.351415108
## 26818 0.56576525 0.3594562 0.074778512
## 30856 0.42168270 0.4455203 0.132797026
## 16225 0.21147986 0.3076720 0.480848117
## 30552 0.40347627 0.5191043 0.077419431
## 528 0.52627884 0.3843093 0.089411837
## 90279 0.67072448 0.2756639 0.053611627
## 74686 0.62551640 0.3009091 0.073574456
## 663 0.01238009 0.9859554 0.001664465
## 96403 0.45450454 0.5112315 0.034263965
## 65228 0.32728827 0.6053021 0.067409656
## 101266 0.62773691 0.3211063 0.051156833
## 59056 0.59798356 0.3256124 0.076404017
## 105495 0.33059624 0.3358948 0.333508959
## 60043 0.33437538 0.4956896 0.169935034
## 86011 0.58253232 0.3371441 0.080323533
## 30481 0.31115649 0.4757809 0.213062626
## 66329 0.70210420 0.2636330 0.034262762
## 107917 0.44006086 0.4559084 0.104030742
## 28476 0.01238009 0.9859554 0.001664465
## 22232 0.75050800 0.2257358 0.023756155metriks
# 1. silhouette (-1 to 1) higher is better
mean(silhouette(km_res$cluster, dist(data_scaled))[,3])## [1] 0.1960999mean(silhouette(kmed_res@cluster, dist(data_scaled))[,3])## [1] -0.01226353mean(silhouette(db_res$cluster, dist(data_scaled))[,3])## [1] -0.1356254