r - Clustering with PAM not isolating clusters but T-SNE shows well formed clusters -


i building clustering algorithm use data have not yet seen, i'm using psuedo data in mean time. results pam show not have isolated clusters ggplot using tsne shows have well-formed clusters. suspect due fake data. have thoughts why be?

here data , please note, age , howold represent different things:

library(dplyr) library(cluster) library(rtsne) library(ggplot2)  set.seed(1987) n = 350 clust_dat <-  data.frame(personid = 1:n,          networkpref = sample(c("topic", "jobtitle", "orgtype"),                              size = n, replace = true,                              prob = c(0.56, 0.20, 0.24)),          age = sample(23:65, size = n, replace = true),          familyimp = sample(c(1, 2, 3, 4, 5), size = n, replace = true,                              prob = c(0.02, 0.01, 0.10, 0.4, 0.83)),          howold = sample(25:30, size = n, replace = true,                          prob = c(.40, .30, .20, .05, .03, .02)),          horror = sample(c("yes", "no"), size = n, replace = true,                           prob = c(0.27, 0.73)),          sailboat = sample(c("yes", "no"), size = n, replace = true,                             prob = c(0.58, 0.42)))

here model build after first defining levels of ordinal variable

clust_dat$familyimp <- factor(clust_dat$familyimp,                            levels = c("1", "2", "3", "4", "5"),                            ordered = true)  gower_dist <- daisy(clust_dat[, -1], metric = "gower") gower_matrix <- as.matrix(gower_dist)  #find silhouette width many pam models sil_width <- c(na) (i in 2:ceiling(nrow(clust_dat)/9)) {    pam_fit <- pam(gower_dist,                   diss = true,                  k = i)   sil_width[i] <- pam_fit$silinfo$avg.width }  #build pam model best silhouette width pam_fit <- pam(gower_dist, diss = true, k = which.max(sil_width))

when getting isolation info on pam, get:

pam_fit$isolation   1  2  3  4  5  6  7  8  9 10 11 12  no no no no no no no no no no no no  levels: no l l*

but plotting shows some formed clusters

tsne_obj <- rtsne(gower_dist, is_distance = true)  tsne_data <-    tsne_obj$y %>%   data.frame() %>%   setnames(c("x", "y")) %>%   mutate(cluster = factor(pam_fit$clustering),          name = clust_dat$personid)  ggplot(tsne_data, aes(x = x, y = y)) +   geom_point(aes(color = cluster))

any ideas? if remove continuous variables non-defined clusters recognized isolated...

the way generate data, should not have clusters beyond artifact categoricial labels used. based on frequencies used, have expect 8 "clusters" corresponding trivial combinations of attributes.

if generate i.i.d. data, not supposed cluster!

so i'd rather assume visualization problem.

see, e.g., this answer on problems of "seeing" clusters in tsne.


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