On 26.09.2007, at 13:46, Olena Morozova wrote:
> I am very new to R and statistical analysis in general. I am trying
> to plot
> a matrix of several hundred rows against a vector of 4 values. This
> all has
> to be on the same graph with different rows represented by
> different color.
> Thi
On 26.09.2007, at 09:54, Prof Brian Ripley wrote:
> On Wed, 26 Sep 2007, Friedrich Leisch wrote:
>
>>>>>>> On Tue, 25 Sep 2007 20:16:05 -0400,
>>>>>>> Wiebke Timm (WT) wrote:
>>
>> > You might want to check if there is a neural
You might want to check if there is a neural gas algorithm in R.
kmeans generally has a high variance since it is very dependent on
the initialization. Neural gas overcomes this problem by using a
ranked list of neighbouring data points instead using data points
directly. It is more stable (
Thanks for your answer!
On 20.09.2007, at 12:48, Tim Hesterberg wrote:
> Might you be having numerical problems?
That might very well be what's happening. Did hope that it only
happens late in the procedure so I can ignore it, but those Cp values
indicate I maybe can't.
> If you're using th
Hi!
Ok, probably my last mail was too long. Questions are:
* Did someone try lars on data with much more components than data
points? Did you observe bad overfitting, too? Any other observations?
* Why might the lars (least angle regression from lars package)
method produce beta values that
On 20.09.2007, at 09:24, Rob Kabacoff wrote:
> I hope that you find this useful. Please feel free to link to the
> site.
Very nicely done from what I saw by browsing the site a little. Good
colors, good content, easy to navigate. Thanks!
You might want to add self-organizing maps as a cross-
Hi!
When I apply the lars (least-angle-regression) method to my data
(3655 features, only 355 data points, no I did not mistype), I
observe a strange behaviour:
1) The beta values tend to grow into real high values quite fast up
to a point where they overflow and get negative. The overflow
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