Displaying 20 results from an estimated 20000 matches similar to: "cluster validation"
2006 May 02
1
Cluster validation methods
Hi All,
Except the "Rand Index", "Dunn Index" and "Silhouette width", are there
other cluster validation methods in R? Could you please also specify the
function?
Thanks!
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2006 Mar 20
1
plot and validation in clustering
Hi there,
I use function "kmeans" and "clara" to cluster one flow cytometry
dataset. By using function "plot", the clusters got from "clara" can be
graphed, while "kmeans" not. How can I get the plot of the clusters of
"kmeans"?
And, I hope to compare the two methods "kmeans" and "clara", or in other
word, I
2004 Apr 26
0
Cluster validation statistics in fpc
Hi,
this is to announce a new version (1.1-2) of my package fpc. Apart from
the stuff already present in the older version (methods for fixed point
clustering and clusterwise regression, somewhat bug-cleaned and with
faster examples) there is now a function cluster.stats, which computes
some distance-based statistics often used for cluster validation,
description and decision about the number of
2004 Apr 26
0
Cluster validation statistics in fpc
Hi,
this is to announce a new version (1.1-2) of my package fpc. Apart from
the stuff already present in the older version (methods for fixed point
clustering and clusterwise regression, somewhat bug-cleaned and with
faster examples) there is now a function cluster.stats, which computes
some distance-based statistics often used for cluster validation,
description and decision about the number of
2006 Jan 07
1
Clustering and Rand Index
Dear WizaRds,
I am trying to compute the (adjusted) Rand Index in order to comprehend
the variable selection heuristic (VS-KM) according to Brusco/ Cradit
2001 (Psychometrika 66 No.2 p.249-270, 2001).
Unfortunately, I am unable to correctly use
cl_ensemble and cl_agreement (package: clue). Here is what I am trying
to do:
library(clue)
## Let p1..p4 be four partitions of the kind
2006 Feb 27
1
clustering
Hi there,
Sorry for the double email. Does R have the packages for the following
clustering methods? And if it does, what the commands for them?
1. SOM (Self-organization map)
2. Graph partitioning:
3. Neural network
4. Probability Binning
Thank you very much!
Linda
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2010 Feb 11
0
cluster/distance large matrix (fwd)
On Thu, 11 Feb 2010, Christian Hennig wrote:
>It is well know that hierarchical methods are problematic with too large
>dissimilarity matrices; even if you resolve the memory problem, the number of
>operations required is enormous.
There is at least one exception to this. Single-linkage hierarchical clustering with a convex distance such as Euclidean distance is feasible for quite
2006 Mar 16
1
about pam
Hi there,
In the description of command "pam", it mentions "For datasets larger
than (say) 200 observations". Now my dataset is a "54732 by 5" dataframe
named "test". When I try to run pam(test,4),it shows " cannot allocate
vector of length 1497768547". Is it because the row too big that it
can't handle?
Thank you!
2005 Jun 16
1
Survey - Cluster Sampling
Dear WizaRds,
I am struggling to compute correctly a cluster sampling design. I want
to do one stage clustering with different parametric changes:
Let M be the total number of clusters in the population, and m the
number sampled. Let N be the total of elements in the population and n
the number sampled. y are the values sampled. This is my example data:
clus1 <-
2008 Jan 14
0
clusterwise regression from fpc (fixed point clustering) package
hi there, whenever i try the clusterwise regression from the fpc package, there occurs the following problem:
the first cluster is always designed in a way, that when i run a normal linear regression on the independent variables to describe the dependent variable (only on those respondents from the first cluster) - then the regression uses only one independent variable that describes the whole
2008 Mar 18
3
Partition data into clusters
Greetings R-users,
I have been using the fpc package in R to cluster my data. Speficically I am
using kmeansruns clustering.
I would like to know how I use R to partition data into clusters. What I am
doing is as follows.
# Use csv file as input
#####################
wholeset = read.csv("Spellman800genesImputed.csv")
# exclude first col (gene names)
##########################
2006 Apr 01
1
reference paper about SOM
Hi All,
I'm looking for some reference paper about SOM (self organizing map)
algorithm. I tried the paper which is mentioned in
the help page of function "som (package:som)":
http://www.cis.hut.fi/research/papers/som_tr96.ps.Z
But I can't open it for some reason. Could you please help me with it ?
Thanks a lot!
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2006 Jul 17
1
use "factor" for categorical covariate in Cox PH model
Hi All,
I'm learning the R codes for Cox PH modeling. Could I ask you what the
function of "factor" in modeling? Thank you!
When dealing with the categorical covariates (for example 3 groups), it
will come out different results if we add the command "factor" in front
of the categorical covariate or not: if we don't add "factor", there is
only one
2008 Jun 13
3
cluster.stats
Dear list,
I just tried to use the function cluster.stat in the package fpc.
I just have a couple of questions about the syntax:
cluster.stats(d,clustering,alt.clustering=NULL,
silhouette=TRUE,G2=FALSE,G3=FALSE)
1) the distance object (d) is an object obtained by the function dist() on
my own original matrix?
2) clustering is the clusters vector as result of one of the many clustering
methods?
2006 Apr 05
1
"partitioning cluster function"
Hi All,
For the function "bclust"(e1071), the argument "base.method" is
explained as "must be the name of a partitioning cluster function
returning a list with the same components as the return value of
'kmeans'.
In my understanding, there are three partitioning cluster functions in
R, which are "clara, pam, fanny". Then I check each of them to
2008 Dec 17
1
bug (?!) in "pam()" clustering from fpc package ?
Hello all.
I wish to run k-means with "manhattan" distance.
Since this is not supported by the function "kmeans", I turned to the "pam"
function in the "fpc" package.
Yet, when I tried to have the algorithm run with different starting points,
I found that pam ignores and keep on starting the algorithm from the same
starting-points (medoids).
For my
2005 Jan 03
0
speed of the cluster.stats function
Hello list (happy new yeaR),
Here's a copy of a message i just send to Christian Hennig (who wrote
the fpc package).
That may interrest some of you, and maybe someone could have a better
solution than mine.
Romain.
------------------------------------------------------------------------------------------
Mister Hennig,
[[[ I'm writing in english because i don't know german
2006 Jan 08
1
Clustering and Rand Index - VS-KM
Dear WizaRds,
I have been trying to compute the adjusted Rand index as by Hubert/
Arabie, and could not correctly approach how to define a partition
object as in my last request yesterday.
With package fpc I try to work around the problem, using my original data:
mat <- matrix( c(6,7,8,2,3,4,12,14,14, 14,15,13,3,1,2,3,4,2,
15,3,10,5,11,7,13,6,1, 15,4,10,6,12,8,12,7,1), ncol=9, byrow=T )
2013 Nov 16
0
selecting optimal cluster validation score
Hi:
I have calculated the Silhouette score and Dunn score after
hierarchical clustering for 3 clusters:
#Distance measure
d <- dist(USArrests, method = "euclidean")
#Hierarchical clustering
hc <- hclust(dist(USArrests), "ave")
#calculating silhouette value for 3 clusters
sil<- silhouette(cutree(hc, k=3), d)
#calculating Dunn index for 3 clusters
clus <- cutree(hc,
2006 Oct 17
4
cluster in R
hi,
is there some good summary on clustering methods in R? It seems there
are many packages involving it.
And I have two questions on clustering here:
1. Is there a way of evaluate the effecitives (or seperation) of
clustering (rather than by visualization)?
2. Is there a search method (like genetic search) which can help find
the best subset of attributes which gives best seperation?
Thanks,