Hi,
R has a vast array of tools for cluster analysis. There's even a task
view: https://cran.r-project.org/web/views/Cluster.html
Which method is best for your needs is going to require you spending
some time working to understand the pros and cons, and possibly
consulting with a local
Hi,
I have data from farmers with different variables. I would like to classify
them according to some variables. Can you help me with "R" to find the best
variables to classify them and how to classify them with "R". Some variables
are numerical others are ordinal.
Best regards,
Bienvenue
Hi Tina,
What's wrong with what you did?
The output object of som() contains the classification of each sample.
You probably do need to read more about self-organizing maps, since
you specified you wanted the samples classified into nine groups, and
that's unlikely to be your actual intent.
I
Search!
the rseek.org site gives many hits for "self organizing maps", including
the som package among others.
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic
Dear All,
Who can I use Self Organizing Map (SOM) results to cluster samples? I have
tried following but this gives me only the clustering of grids, while I
want to cluster (150) samples:
library(kohonen)
iris.sc <- scale(iris[, 1:4])
iris.som <- som(iris.sc, grid=somgrid(xdim = 3, ydim=3,
: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Luigi
Marongiu
Sent: Friday, 17 February 2017 02:31
To: r-help
Subject: [R] cluster data in lattice dotplot and show stdev
dear all,
i have a set of data that is separated in the variables: cluster (two
runs), type (blank, negative a
Hi Luigi,
Are you looking for something like this?
library(plotrix)
ylim=c(0,1.7)
png("lmplot.png",width=600,height=300)
par(mfrow=c(1,2))
brkdn.plot(value~type,data=my.data[my.data$target=="A",],
main="Run 1",ylab="Value",xlab="",xaxlab="target",ylim=ylim,
dear all,
i have a set of data that is separated in the variables: cluster (two
runs), type (blank, negative and positive) and target (A and B), each
duplicated. I am plotting it with lattice and the result is a 2x2 matrix
plot in which the top two cells (or panels) are relative to run 2, the
Hi! All.
I'm not much familiar with R.
So I tried to find a R function or packages that could work with my problems.
What I wonder is,
Whether there is any R function or package that includes the cluster analysis
considering with the weighted attribute.
I saw several papers that dealt
Hi
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Venky
Sent: Wednesday, June 17, 2015 8:43 AM
To: R Help R
Subject: [R] cluster analysis
Hi friends,
I have data like this
In R or elsewhere?
Group
Employee size WOE Employee size2
Hi friends,
I have data like this
Group
Employee size WOE Employee size2 Weight of Evidence 1081680995 0
0.12875537 0.128755 -0.30761 1007079896 1 0.48380133 -0.46544 -0.70464
1000507407 2 0.26029825 -0.46544 0.070221 1006400720 3 0.12875537 0.128755
0.151385 1006916029 4 0.12875537 -0.05955
Dear Sun Shine,
dtes - dist(tes.df, method = 'euclidean')
dtesFreq - hclust(dtes, method = 'ward.D')
plot(dtesFreq, labels = names(tes.df))
However, I get an error message when trying to plot this: Error in
graphics:::plotHclust(n1, merge, height, order(x$order), hang, : invalid
dendrogram
Hi list
I am using the 'tm' package to review meeting notes at a school to
identify terms frequently associated with 'learning', 'sports', and
'extra-mural' activities, and then to sort any terms according to these
three headers in a way that could be supported statistically (as opposed
to,
Bert,
Thank you for the suggestion but I am familiar with the clustering routines in
R. My issue is how to carry out a grouping analysis on multi variate data that
includes postcode shape file data as a variable.
Rather than obtain clusters spread across the map I am looking to limit the
I am looking to cluster some data including a postcode shape file but need to
ensure that the resulting groups are contiguous.
How do I accomplish this using R?
Kind Regards
Dr Graham Leask
Economics Strategy Group
Aston University
Aston Triangle
Birmingham
B4 7ET
Tel: 0121 204 3150
Have you looked at the Cluster task view on CRAN?
http://cran.r-project.org/web/views/
-- Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom.
Clifford Stoll
On Sun, Mar 8, 2015 at
On 2014-11-05 14:50, Therneau, Terry M., Ph.D. wrote:
This is fixed in version 2.37-8 of the survival package, which has been
in my send to CRAN real-soon-now queue for 6 months. Your note is a
prod to get it done. I've been updating and adding vignettes.
Is your fixed code publicly
This is fixed in version 2.37-8 of the survival package, which has been in my send to
CRAN real-soon-now queue for 6 months. Your note is a prod to get it done. I've been
updating and adding vignettes.
Terry Therneau
On 11/05/2014 05:00 AM, r-help-requ...@r-project.org wrote:
I am
Dear All,
I have clustered a patient data set by agnes.
I want to extract information for each cluster, I.E. all row ids
belonging to each cluster.
Thank you.
[[alternative HTML version deleted]]
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R-help@r-project.org mailing list
On 24/09/14 16:13, Sohail Khan wrote:
Dear All,
I have clustered a patient data set by agnes.
I want to extract information for each cluster, I.E. all row ids
belonging to each cluster.
Fascinating, thank you for sharing.
Best,
Bart
__
of Anthropology
Texas AM University
College Station, TX 77840-4352
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Sohail Khan
Sent: Wednesday, September 24, 2014 9:14 AM
To: r-help@r-project.org
Subject: [R] Cluster -- Agnes function
Dear
My purpose involves creating a dissimilarity matrix using the daisy package
in R before applying k-mediod clustering for customer segmentation. The
dataset has 133,153 observations of 35 variables in a data.frame with
numerical, categorical, blank cells and missing values. Missing values
refer to
Dear R-list,
I am currently working on a dataset with a colleague who uses stata.
We fit a random intercept model to the data (decisions clustered in
participants) and get closely the same results in stata (using xtreg re) and R
(using the lme4 or multilevel package).
Now in stata, there is
On Oct 15, 2013, at 3:32 AM, Martin Batholdy wrote:
Dear R-list,
I am currently working on a dataset with a colleague who uses stata.
We fit a random intercept model to the data (decisions clustered in
participants) and get closely the same results in stata (using xtreg
re) and R (using
Group - I'm having problems with the 'cluster' package. Installation
appears successful but attempts to load it with either library() or
require() result in the error message
Error in library(cluster) : there is no package called ‘cluster’
All that appears to be installed is cluster.dll in
On 15.07.2013 23:51, David Stevens wrote:
Group - I'm having problems with the 'cluster' package. Installation
appears successful but attempts to load it with either library() or
require() result in the error message
Error in library(cluster) : there is no package called ‘cluster’
All that
I want to do Agglomerative Hierarchical clustering using complete linkage
method in R using the function agnes or hclust.
1. Can i do a cluster analysis of h=(n+p+1)/2 out of n observation? note that
p=nomber of variables(dependent and independent)
2. Can i plot the dendrogram and get the
Hello,
I'm just a beginner and probably there is a better way to do it but here it
goes:
#cluster analysis
Euclidean_Distance - dist(mydata, method=euclidean, diag=FALSE
, upper=FALSE, p=2)
data - hclust(Euclidean_Distance, method=ward, members=NULL)
plot(data,hang=-1)
#K=4 # i chose to
Hi,
I have created a heatmap using heatmap.2 having 7 clusters. I would like
to extract the list of genes that are in these 7 clusters.
Is there any function that can be used to extract genes for each cluster?
Cheers,
Sudhir
--
__
I am doing cluster analysis of my SNPs data. I have 2 questions:
1. I draw the cluster in hclust using the following codes.change direction
to vertical.
data - read.table(as.matrix(file.choose()), header=T, row.names = 1,
sep=\t)
plot(hclust(as.dist(data),method=complete))
it is horizontal,
I am trying to perform cluster analysis on survey data where each respondent
has answered several questions, some of which have categorical answers (blue
pink green etc) and some of which have scale answers (rating from 1 to 10
etc).My problem is that certain age groups were over-sampled and I
On Wed, Mar 20, 2013 at 3:55 AM, Emma Gibson waterbab...@hotmail.comwrote:
I am trying to perform cluster analysis on survey data where each
respondent has answered several questions, some of which have categorical
answers (blue pink green etc) and some of which have scale answers
(rating
Does R have any function for performing cluster analysis when each subject
contributes more than one observation to the analysis, i.e. a repeated measures
cluster analysis? I prefer an agglomerative clustering, but would certainly be
happy with a K-mean or other clustering technique. To the
On 22.02.2013 11:41, Bob Green wrote:
Hello,
In SPSS the cluster analysis output includes an agglomerations schedule,
which details the stages when cases are joined.
Is it possible to obtain such output when performing cluster analysis in
R? If so, I'd appreciate advice regarding how to
Hello Uwes,
Thanks. Re-reading the hclust pages I found that using the hclust
'USArrests' data that the command plot (hc1) will generate the
order in which cases joined. however, I still can't see how to obtain
the respective height at which each case joined each cluster or the
height
To: Uwe Ligges
Cc: r-help@r-project.org
Subject: Re: [R] Is it possible to obtain an agglomeration schedule with R
cluster analyis
Hello Uwes,
Thanks. Re-reading the hclust pages I found that using the hclust
'USArrests' data that the command plot (hc1) will generate the
order
tibco.com
-Original Message-
From: r-help-boun...@r-project.org
[mailto:r-help-boun...@r-project.org] On Behalf
Of Bob Green
Sent: Saturday, February 23, 2013 12:49 PM
To: Uwe Ligges
Cc: r-help@r-project.org
Subject: Re: [R] Is it possible to obtain an agglomeration
schedule with R
Hello,
In SPSS the cluster analysis output includes an agglomerations
schedule, which details the stages when cases are joined.
Is it possible to obtain such output when performing cluster analysis
in R? If so, I'd appreciate advice regarding how to obtain this information.
Any
Hello everyone,
I mail you because of my lake of knowlegde regarding statistics.
I'm using the CA and PCoA (but maybe should I use some other techniques) to
determine the differences and similarities between a large sample of plants
using different kind of traits through matrix of mixte
I am following instructions online for cluster analysis using the mclust
package, and keep getting errors.
http://www.statmethods.net/advstats/cluster.html
These are the instructions (there is no sample dataset unfortunately):
# Model Based Clustering
library(mclust)
fit - Mclust(mydata)
It's hard to answer these questions without knowing what the errors are and
how they can be reproduced.
Best, Ingmar
On Thu, Nov 22, 2012 at 1:03 AM, KitKat katherinewri...@trentu.ca wrote:
Thanks, I have been trying that site and another one
(http://www.statmethods.net/advstats/cluster.html)
These are the errors I've been having. I have been trying 3 different things
1- Mclust:
This is the example I have been following:
# Model Based Clustering
library(mclust)
fit - Mclust(mydata)
plot(fit, mydata) # plot results
print(fit) # display the best model
What I have done:
fit -
Thank you for replying!
I made a new post asking if there are any websites or files on how to
download package mclust (or other Bayesian cluster analysis packages) and
the appropriate R functions? Sorry I don't know how this forum works yet
--
View this message in context:
http://cran.r-project.org/web/views/Cluster.html
might be a good start
Brian
On Nov 21, 2012, at 1:36 PM, KitKat wrote:
Thank you for replying!
I made a new post asking if there are any websites or files on how to
download package mclust (or other Bayesian cluster analysis packages) and
Thanks, I have been trying that site and another one
(http://www.statmethods.net/advstats/cluster.html)
I don't know if I should be doing mclust or mcclust, but either way, the
codes are not working. I am following the guidelines online at:
mcclust -
, www.homepages.ucl.ac.uk/~ucakche
From: r-help-boun...@r-project.org [r-help-boun...@r-project.org] on behalf of
KitKat [katherinewri...@trentu.ca]
Sent: 15 November 2012 18:14
To: r-help@r-project.org
Subject: [R] cluster analysis in R
I have two issues.
1-I am trying
I have two issues.
1-I am trying to use morphology to identify gender. I have 9 variables, both
continuous and categorical. I was using two-step cluster analysis in SPSS
because two-step could deal with different types of variables. But the
output tells me that an animal is in cluster 1 or 2, it
Dear KitKat,
After installing R and reading some introductory material on getting
started with R you may want to check the CRAN task view on cluster analysis:
http://cran.r-project.org/web/views/Cluster.html
which has many useful references to all kinds and flavors of clustering
techniques,
Have a look at the package mclust.
Jose
From: r-help-boun...@r-project.org [r-help-boun...@r-project.org] On Behalf Of
Ingmar Visser [i.vis...@uva.nl]
Sent: 15 November 2012 21:10
To: KitKat
Cc: r-help@r-project.org
Subject: Re: [R] cluster analysis in R
Frederico,
This is not exactly what you're after, but perhaps it will help. In this
example I fit a cluster analysis to the data, then I cut the tree at a
height of 3 (you would do this with your data at a height of 40). It's
not a perfect solution, but it might be good enough, depending on
Hello:
What I want to do is quite simple, but I can't find a way.
I have a data frame with several points (x and y coords). I want to add
another column with cluster membership. For example aggregate all the points
that stand within a distance of 40 from each other.
I've tried using
Hi,
okay, and which algorithm is it? I had a closer look at the manual and could
not find it, but there is quite a number of methods in there, maybe I missed
it.
Thanks,
Martin
--
View this message in context:
Hi all,
Does anyone know a cluster algorithm in R that allows to set the
cluster size (not the number of clusters) to a fixed value?
With best regards,
Martin
--
Dipl-Inf. Martin Gütlein
Phone:
+49 (0)761 203 7633 (office)
+49 (0)177 623 9499 (mobile)
Email:
Hi,
See the package cluster in R.
Ozgur
--
View this message in context:
http://r.789695.n4.nabble.com/cluster-algorithm-with-fixed-cluster-size-tp4632523p4632540.html
Sent from the R help mailing list archive at Nabble.com.
__
R-help@r-project.org
-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Maria Froes
Sent: Wednesday, May 30, 2012 6:42 PM
To: r-help@r-project.org
Subject: Re: [R] cluster with mahalanobis distance
How can I perform cluster analysis using the mahalanobis distance
instead
How can I perform cluster analysis using the mahalanobis distance instead of
the euclidean distance?
Thank you
Maria Froes
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
From: r-help-boun...@r-project.org [r-help-boun...@r-project.org] on behalf of
Taisa Brown [taisa.br...@unb.ca]
Sent: 15 April 2012 03:28
To: r-help@r-project.org
Subject: [R] Cluster Analysis
Hi,
I was wondering what the best equivalent to SAS's FASTCLUS
Associate Professor of Anthropology
Texas AM University
College Station, TX 77843-4352
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Taisa Brown
Sent: Saturday, April 14, 2012 7:29 PM
To: r-help@r-project.org
Subject: [R] Cluster
Hi,
I was wondering what the best equivalent to SAS's FASTCLUS and PROC CLUSTER
would be. I need to be able to test the significance of the clusters by
comparing the probability of obtaining an equal or greater pseudo F to the
Bonferroni-corrected level. I will also need to plot r squared
Hello,
I want to do a cluster analysis with my data. The problem is, that the
variables dont't consist of single value but the entries are pairs of
values.
That lokks like this:
Variable 1:Variable2: Variable3: ...
(1,2) (1,5) (4,2)
(7,8) (3,88)
Sent: Wednesday, April 04, 2012 6:32 AM
To: r-help@r-project.org
Subject: [R] cluster analysis with pairwise data
Hello,
I want to do a cluster analysis with my data. The problem is, that the
variables dont't consist of single value but the entries are pairs of
values.
That lokks like
On Wed, Apr 04, 2012 at 01:32:10PM +0200, paladini wrote:
Hello,
I want to do a cluster analysis with my data. The problem is, that the
variables dont't consist of single value but the entries are pairs of
values.
That lokks like this:
Variable 1:Variable2: Variable3: ..
On Wed, Apr 4, 2012 at 10:12 AM, Petr Savicky savi...@cs.cas.cz wrote:
On Wed, Apr 04, 2012 at 01:32:10PM +0200, paladini wrote:
Var1 - c((1,2), (7,8), (4,7))
Var2 - c((1,5), (3,88), (12,4))
Var3 - c((4,2), (6,5), (4,4))
DF - data.frame(Var1, Var2, Var3, stringsAsFactors=FALSE)
If you
For a school course I and a partner developed a GUI in R designed to
enable exploration of data via visualization of hierarchical
clustering and correlation of cluster partitions with external
metadata. The key features were the ability to load in a distance
matrix (most GUI-based clustering
Hi,
I need to make a cluster classification by the unique values of the data frame.
I explain the problem. I need to classify this table, and assign to
the same cluster each row that has the same combination of value:
data1
layer_1 layer_2 layer_3
[1,] 0.246000 2
Your data1 and your data1_class file differ in the first three
columns. Assuming that's an error, here's one way to do it:
data1 - data.frame(layer1=c(.2, .5, .2, .8, .2, .5, .5, .8, .2,
.8),layer2=c(2,3,2,2,1,2,3,2,2,2), layer3=c(1,1,1,1,1,1,1,1,1,4))
data1 - cbind(data1,
Also read FAQ 7.31 before using 'numerics' as grouping factors.
On Mon, Jul 18, 2011 at 6:36 AM, Sarah Goslee sarah.gos...@gmail.com wrote:
Your data1 and your data1_class file differ in the first three
columns. Assuming that's an error, here's one way to do it:
data1 -
On Mon, Jul 18, 2011 at 06:36:13AM -0400, Sarah Goslee wrote:
Your data1 and your data1_class file differ in the first three
columns. Assuming that's an error, here's one way to do it:
data1 - data.frame(layer1=c(.2, .5, .2, .8, .2, .5, .5, .8, .2,
.8),layer2=c(2,3,2,2,1,2,3,2,2,2),
Addition of a cluster() term fits a Generalized Estimating Equations
(GEE) type of model, addition of frailty() fits a random effects model
(Mixed Effect or ME). In glm analysis (linear regression, logistic
regression, etc) the arguments about the advantages/disadvantages of GEE
ve ME would
Dear List,
Can anyone please explain the difference between cluster() and
frailty() in a coxph? I am a bit puzzled about it. Would appreciate
any useful reference or direction.
cheers,
Ehsan
marginal.model - coxph(Surv(time, status) ~ rx + cluster(litter), rats)
frailty.model -
Hi Ehsan,
My understanding (hopefully someone will jump in if this is wrong) is
that cluster() identifies a variable that is an indicator for
correlated observations (rats in a litter, children in a classroom,
etc.). The relative risk from treatment (rx) is for a random sample
of rats.
Dear all,
I'm modelling extreme rainfall,particularly those that lie above a threshold
was searching for a suitable package in R which may enable a cluster
analysis on those extreme events and would really appreciate for any
suggestions.
Thanks,
Fir
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
Dear Hans,
clara doesn't require a distance matrix as input (and therefore doesn't
require you to run daisy), it will work with the raw data matrix using
Euclidean distances implicitly.
I can't tell you whether Euclidean distances are appropriate in this
situation (this depends on the
On Thu, Mar 31, 2011 at 07:06:31PM +0100, Christian Hennig wrote:
Dear Hans,
clara doesn't require a distance matrix as input (and therefore
doesn't require you to run daisy), it will work with the raw data
matrix using
Euclidean distances implicitly.
I can't tell you whether Euclidean
On Thu, Mar 31, 2011 at 08:48:02PM +0200, Hans Ekbrand wrote:
On Thu, Mar 31, 2011 at 07:06:31PM +0100, Christian Hennig wrote:
Dear Hans,
clara doesn't require a distance matrix as input (and therefore
doesn't require you to run daisy), it will work with the raw data
matrix using
On Thu, Mar 31, 2011 at 11:48 AM, Hans Ekbrand h...@sociologi.cjb.net wrote:
The variables are unordered factors, stored as integers 1:9, where
1 means Full-time employment
2 means Part-time employment
3 means Student
4 means Full-time self-employee
...
Does euclidean distances make
Peter Langfelder wrote:
On Fri, Nov 26, 2010 at 6:55 AM, Derik Burgert derik2...@yahoo.de wrote:
Dear list,
running a hierachical cluster analysis I want to define a number of
objects that build a cluster already. In other words: I want to force
some of the cases to be in the same
Dear list,
running a hierachical cluster analysis I want to define a number of objects
that build a cluster already. In other words: I want to force some of the cases
to be in the same cluster from the start of the algorithm.
Any hints? Thanks in advance!
Derik
[[alternative HTML
On Fri, Nov 26, 2010 at 6:55 AM, Derik Burgert derik2...@yahoo.de wrote:
Dear list,
running a hierachical cluster analysis I want to define a number of objects
that build a cluster already. In other words: I want to force some of the
cases to be in the same cluster from the start of the
Hi Ulrich,
I'm studying the principles of Affinity Propagation and I'm really glad to
use your package (apcluster) in order to cluster my data. I have just an
issue to solve..
If I apply the funcion: apcluster(sim)
where sim is the matrix of dissimilarities, sometimes I encounter the
warning
Pablo, we've had success using
http://mephisto.unige.ch/traminer/preview.shtml to look at marketing paths.
Question would be how many distinct case step discriptions are there?
HTH, Jim
On Jul 26, 2010 9:44 AM, Pablo Cerdeira pablo.cerde...@gmail.com wrote:
Hi all,
I have no idea if this
Hi Allan,
It helps a lot. I´ll try to read more about it.
But, as you asked me, here goes a brief explanation about the necessary
columns of the sample date paste at the end:
id_processo: identify a legal case, it is its primary key.
ordem_andamento: is the step number inside a legal case
Hi Jim,
Ow! Very nice job at http://mephisto.unige.ch/traminer/preview.shtml I´m
going to read more about it.
I have a lot of different steps, in a sequence. Actually, 586 different
possible steps, but I have 4269 legal cases, with a maximum of 379 steps
each one.
If you want, I can send this
Hi all,
I have no idea if this question is to easy to be answered, but I´m starting
with R. So, here we go.
I have a large dataset with a lot of steps a judicial case. A sample is
attached.
I´d like to do a cluster analysis to try to understand with one is the most
usual path followed by this
abanero wrote:
Do you know something like “knn1” that works with categorical variables
too?
Do you have any suggestion?
There are surely plenty of clustering algorithms around that do not require
a vector space structure on the inputs (like KNN does). I think
agglomerative clustering would
Dear abanero,
In principle, k nearest neighbours classification can be computed on
any dissimilarity matrix. Unfortunately, knn and knn1 seem to assume
Euclidean vectors as input, which restricts their use.
I'd probably compute an appropriate dissimilarity between points (have a
look at
Hi,
thank you Joris and Ulrich for you answers.
Joris Meys wrote:
see the library randomForest for example
I'm trying to find some example in randomForest with categorical variables
but I haven't found anything. Do you know any example with both categorical
and numerical variables? Anyway I
Hi Abanero,
first, I have to correct myself. Knn1 is a supervised learning algorithm, so
my comment wasn't completely correct. In any case, if you want to do a
clustering prior to a supervised classification, the function daisy() can
handle any kind of variable. The resulting distance matrix can
@r-project.org
Subject
Re: [R] cluster analysis and
05/27/2010 07:56 supervised classification: an
AMalternative to knn1?
Hi
I had a look at the documentation of the package apcluster.
That's interesting but do you have any example using it with both
categorical
and numerical variables? I'd like to test it with a large dataset..
Your posting has opened my eyes: problems where both numerical and
categorical
Sorry, Joris, I overlooked that you already mentioned daisy() in your
posting. I should have credited your recommendation in my previous message.
Cheers, Ulrich
--
View this message in context:
Ulrich wrote:
Affinity propagation produces quite a number of clusters.
I tried with q=0 and produces 17 clusters. Anyway that's a good idea,
thanks. I'm looking to test it with my dataset.
So I'll probably use daisy() to compute an appropriate dissimilarity then
apcluster() or another
Christian wrote:
and the implement
nearest neighbours classification myself if I needed it.
It should be pretty straightforward to implement.
Do you intend modify the code of the knn1() function by yourself?
No; if you understand what the nearest neighbours method does, it's not
very
What do you suggest in order to assign a new observation to a determined
cluster?
As I mentioned already, I would simply assign the new observation to the
cluster to whose exemplar the new observation is most similar to (in a
knn1-like fashion). To compute these similarities, you can use the
Hi,
I have a 1.000 observations with 10 attributes (of different types: numeric,
dicotomic, categorical ecc..) and a measure M.
I need to cluster these observations in order to assign a new observation
(with the same 10 attributes but not the measure) to a cluster.
I want to calculate for
Not a direct answer, but from your description it looks like you are better
of with supervised classification algorithms instead of unsupervised
clustering. see the library randomForest for example. Alternatively, you can
try a logistic regression or a multinomial regression approach, but these
Dear Dario Sacco,
DS == Dario Sacco dario.sa...@unito.it
on Thu, 06 May 2010 17:45:30 +0200 writes:
DS Dear Dr. Maechler,
DS I am an agronomist and a researcher at the University of Turin. I am
DS also teaching Applied statistics, then I have some knowledge in
DS
Hello everyone!
My data is composed of 277 individuals measured on 8 binary variables
(1=yes, 2=no).
I did two similar cluster analyses, one on SPSS 18.0 and one on R 2.9.2. The
objective is to have the means for each variable per retained cluster.
1) the R analysis ran as followed:
call
Hi Jeoffrey,
How stable are the results in general ?
If you repeat the analysis in R several times, does it yield the same
results ?
Tal
Contact
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Contact me: tal.gal...@gmail.com | 972-52-7275845
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