[R] plot discriminant analysis
David Winsemius
dwinsemius at comcast.net
Wed Oct 14 18:36:59 CEST 2009
On Oct 14, 2009, at 12:24 PM, Alejo C.S. wrote:
> Hi Alain, thanks for the fast response. I've the same results with
> iris
> data, but when I use my data (mentioned in the first message),
You are apparently under the false impression that the data made it
through the listserv. Read the Posting Guide to find out why that
impression is false.
> I have
> different results.
>
> Regards,
>
> Alejo
>
> 2009/10/14 Alain Guillet <alain.guillet at uclouvain.be>
>
>> Hi,
>>
>> I did it with
>>
>> Iris <- data.frame(rbind(iris3[,,1], iris3[,,2], iris3[,,3]), Sp =
>> rep(c("s","c","v"), rep(50,3)))
>> train <- sample(1:150, 75) table(Iris$Sp[train])
>> z <- lda(Sp ~ ., Iris, prior = c(1,1,1)/3, subset = train)
>>
>> Then I did plot(z,xlim=c(-10,10),ylim=c(-10,10)) before drawing
>> points(predict(z)$x,
>> col=palette()[predict(z)$class],xlim=c(-10,10),ylim=c(-10,10)) and
>> all the
>> points are superimposed. The only difference I found was the
>> different x-
>> and y-axis when I drew them separately, i.e.
>> plot(z)
>> plot(predict(z)$x, col=palette()[predict(z)$class])
>>
>>
>> Alain
>>
>>
>>
>> Alejo C.S. wrote:
>>
>>> I'm confused on how is the right way to plot a discriminant
>>> analysis made
>>> by
>>> lda function (MASS package).
>>> (I had attached my data fro reproduction). When I plot a lda
>>> object :
>>>
>>> X <- read.table("data", header=T)
>>>
>>> lda_analysis <- lda(formula(X), data=X)
>>>
>>> plot(lda_analysis)
>>>
>>> #the above plot is completely different to:
>>>
>>> plot(predict(lda_analysis)$x, col=palette()[predict(lda_analysis)
>>> $class])
>>>
>>> that should be the same graph than the first?
>>>
>>> In the second case, I use predict function to obtain the LD1 and LD2
>>> coordinates of lda_analysis (predict(lda_analysis)$x) and it's
>>> respective
>>> class (predict(lda_analysis)$class), but it seems that the classes
>>> are
>>> different:
>>>
>>> table(X$G3, predict(lda_analysis)$class)
>>>
>>> B G M
>>> B 29 0 3
>>> G 0 26 2
>>> M 4 0 46
>>>
>>>
>>> any clues?
>>> Regards,
>>> ------------------------------------------------------------------------
>>>
>>> ______________________________________________
>>> R-help at r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>>
>>
>> --
>> Alain Guillet
>> Statistician and Computer Scientist
>>
>> SMCS - Institut de statistique - Université catholique de Louvain
>> Bureau c.316
>> Voie du Roman Pays, 20
>> B-1348 Louvain-la-Neuve
>> Belgium
>>
>> tel: +32 10 47 30 50
>>
>>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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