Hi Dan, Dylan, Thierry & the rest of the list
Firstly, thanks for your input so far. Unfortunately I am running out of time
as I need to get the analysis complete before IGARSS 09 in Cape Town so I don't
think I will be able to implement your suggestions. In the meantime I have just
selected se
Hi Wesley,
So you just want to partition the 1916 cases into three clusters. This
is a clustering problem rather than a discriminant analysis oriented
classification problem. As a result, Dylan Beaudette's suggestion of
using the clara() function is pretty reasonable, but your data set isn't
so la
See the clara() function from the cluster package. It scales fairly
well to larger-sizes data sets.
Cheers,
Dylan
On Mon, May 11, 2009 at 5:35 AM, Wesley Roberts wrote:
> Hi Dan,
>
> Thanks for the advice. I want to classify my data into three classes; canopy,
> non-canopy and ground based on s
@stat.math.ethz.ch
Onderwerp: Re: [R-sig-Geo] Classification of attribute table
Hi Dan,
Thanks for the advice. I want to classify my data into three classes;
canopy, non-canopy and ground based on six input variables. The input
variables are mean, min, max, median, var, stdev, and kurtosis of
spatially co
Hi Dan,
Thanks for the advice. I want to classify my data into three classes; canopy,
non-canopy and ground based on six input variables. The input variables are
mean, min, max, median, var, stdev, and kurtosis of spatially co-incident
spectra associated with each segment. I have 1916 cases and
Dear R-sig-geo users,
I have the output of a watershed segmentation in vector format (shapefile)
which has it's attribute table populated with statistics regarding spectral
reflectance of each polygon object. The attribute data was sourced from a
geographically co-incident aerial photograph. I
