Displaying 20 results from an estimated 400 matches similar to: "Specifying medoids in PAM?"
2005 May 04
1
Calculate median from counts and values
I am tangled with a syntax question. I want to calculate basic statistics
for a large dataset provided in weights and values and I can't figure out
an elegant way to expand the data.
For example here are the counts:
> counts
n4 n3 n2 n1 p0 p1 p2 p3 p4
1 0 0 0 1 1 3 16 55 24
2 0 0 0 0 2 8 28 47 15
3 1 17 17 13 4 5 12 24 8
...
and the values:
> values
2004 Jun 29
1
give PAM my own medoids
Hello,
When using PAM (partitioning around medoids), I would like to skip the
build-step and give the fonction my own medoids.
Do you know if it is possible, and how ?
Thank you very much.
Isabel
2006 Apr 10
2
passing known medoids to clara() in the cluster package
Greetings,
I have had good success using the clara() function to perform a simple cluster
analysis on a large dataset (1 million+ records with 9 variables).
Since the clara function is a wrapper to pam(), which will accept known medoid
data - I am wondering if this too is possible with clara() ... The
documentation does not suggest that this is possible.
Essentially I am trying to
2008 Feb 22
2
Looping and Pasting
Hello R-community: Much of the time I want to use loops to look at graphs,
etc. For example,
I have 25 plots, for which the names are m.1$medoids, m.2$medoids, ...,
m.25$medoids.
I want to index the object number (1:25) as below (just to show concept).
for (i in 1:25){
plot(m.i$medoids)
}
I've tried the following, with negative results
for ...
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
2009 Mar 29
1
[cluster package question] What is the "sum of the dissimilarities" in the pam command ?
Hello Martin Maechler and All,
A simple question (I hope):
How can I compute the "sum of the dissimilarities" that appears in the pam
command (from the cluster package) ?
Is it the "manhattan" distance (such as the one implemented by "dist") ?
I am asking since I am running clustering on a dataset. I found 7 medoids
with the pam command, and from it I have the
2009 Jun 29
0
Naive knn question
Dear list,
I have two dissimilarity matrices, one for a training data set which I then
clustered using PAM. The second is a diss matrix for a validation data set
(an independent field sample). I have been trying to use knn to distinguish
distances between the validation data set and the 6 mediods of the training
data defined by using PAM.
I continue to get error messages in regards to either the
2008 Aug 01
2
Exporting data to a text file
HI R users
With clara function I get a data frame (maybe this is not the exact word,
I'm new to R) with the following variables:
> names(myclara)
[1] "sample" "medoids" "i.med" "clustering" "objective"
[6] "clusinfo" "diss" "call" "silinfo" "data"
I want to
2011 May 16
1
pam() clustering for large data sets
Hello everyone,
I need to do k-medoids clustering for data which consists of 50,000
observations. I have computed distances between the observations
separately and tried to use those with pam().
I got the "cannot allocate vector of length" error and I realize this
job is too memory intensive. I am at a bit of a loss on what to do at
this point.
I can't use clara(), because I
2011 Aug 10
4
Clustering Large Applications..sort of
Hello all,
I am using the clustering functions in R in order to work with large
masses of binary time series data, however the clustering functions do not
seem able to fit this size of practical problem. Library 'hclust' is good
(though it may be sub par for this size of problem, thus doubly poor for
this application) in that I do not want to make assumptions about the number
of
2010 Oct 25
1
re-vertical conversion of data entries
Dear R user,
Can you please
help me. How do I convert part of a cluster analysis output under the heading “Clustering
vector” as shown below, showing the clusters to which each respondent belongs
to:
[1] 1 1 2 2 1 2 1 2 1 1 2 2 1 2 2 2 2 1 1 1
1 2 2 1 2 2 1 2 2 2 2 2 2 2 2 1 2
[38] 2 1 1 2 2 2 2 2 1 2 1 2 2 2 2 1 2 1 2 2
1 2 2 2 2 2 2 1 2 1 2 2 2 1 1 2 2
[75] 2 1 2 2 2 2 2 2 2 1 1 2
2015 Apr 29
2
cantidad de datos
Hola.
Yo en vez de utilizar análisis cluster que impliquen distancias,
probaría con un kmedias o con un pam (partition around medoids) pero
utilizando muestras, la función clara de la librería cluster puede
ayudarte. Pego el details de la ayuda de 'clara'
Details
clara is fully described in chapter 3 of Kaufman and Rousseeuw (1990).
Compared to other partitioning methods such as pam,
2011 Mar 31
1
Cluster analysis, factor variables, large data set
Dear R helpers,
I have a large data set with 36 variables and about 50.000 cases. The
variabels represent labour market status during 36 months, there are 8
different variable values (e.g. Full-time Employment, Student,...)
Only cases with at least one change in labour market status is
included in the data set.
To analyse sub sets of the data, I have used daisy in the
cluster-package to create
2009 Feb 18
0
Index-G1 error
I am using some functions from package clusterSim to evaluate the best clusters layout.
Here is the features vector I am using to cluater 12 signals:
> alpha.vec
[1] 0.8540039 0.8558350 0.8006592 0.8066406 0.8322754 0.8991699 0.8212891
[8] 0.8815918 0.9050293 0.9174194 0.8613281 0.8425293
In the following I pasted an excerpt of my program:
2015 Apr 29
2
cantidad de datos
El inconveniente con un K-medias, es que se tiene que se tiene que pre definir el número de segmentos, pero eso es algo con lo q no cuento. La solución de Javier me parece q sería la única opción.
Atte.
Ricardo Alva Valiente
-----Mensaje original-----
De: R-help-es [mailto:r-help-es-bounces en r-project.org] En nombre de javier.ruben.marcuzzi en gmail.com
Enviado el: miércoles, 29 de abril de
2001 Nov 23
2
Rose diagrams in R?
I am looking for a function (or package) to plot histograms of directional
data such as wind direction. I believe these are called rose diagrams. Is
there an R script for this? If not, can it be constructed in a function
calling primitive graphic calls (lines, circles, boxes or polygons)?
The stars function is not quite right.
--
David Finlayson
Geomorphogist and GIS Specialist
NearPRISM -
2010 Jun 07
1
classification algorithms with distance matrix
Dear all,
I have a problem when using some classification functions (Kmeans, PAM,
FANNY...) with a distance matrix, and i would to understand how it
proceeds for the positioning of centroids after one execution step.
In fact, in the classical formulation of the algorithm, after each step,
to re-position the center, it calculates the distance between any
elements of the old cluster and its
2015 Apr 29
2
cantidad de datos
Buen aporte?excelente!!
Atte.
Ricardo Alva Valiente
De: Jose Luis Cañadas Reche [mailto:canadasreche en gmail.com]
Enviado el: miércoles, 29 de abril de 2015 12:51 PM
Para: Alva Valiente, Ricardo (RIAV); 'javier.ruben.marcuzzi en gmail.com'; R-help-es en r-project.org
Asunto: Re: [R-es] cantidad de datos
Podrías hacer varios kmedias con diferente número de clusters y comprobar como
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
2004 Jan 14
1
Using pam, agnes or clara as prediction models?
Hello list,
I am new to R, so if the question is rather silly, please ignore it.
I was wondering wether it would be possible to use the models generated
by pam, clara and the like as predictors? Scanning through the available
documentation shed no light (for me) upon the subject.
Regards,
Renald