Hi All,
I've been trying to write my own code for LDA (linear discrim) so I
can modify it to be weighted LDA since some of my groups are outliers.
However, the code I write for standard LDA gives me slightly different
results to those from R (slightly different LDAs.....and not just scalar
differences.
Does R simply invert the pooled within groups scatter matrix e.g. solve(Sw)
and multiply it by the between groups scatter Sb, then take the eigen
vectors?
This is the approach that I use, yet get slightly different
results..........does R by default use a slightly more robust inverse or
estimate of Sw??
I've looked at the source code, and I find it very hard to follow.
If anyone has any ideas that would be great!!
Thanks,
Ben
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