SS-ANOVA for `soft' classification-anct

[Grace Wahba]

The following report is available via anonymous ftp or Mosaic:

ftp://ftp.stat.wisc.edu/pub/wahba/exptl.ssanova.ps.gz

Smoothing Spline ANOVA for Exponential Families, With Application
to the Wisconsin Epidemiological Study of Diabetic Retinopathy

        Grace Wahba, Yuedong Wang, Chong Gu
        Ronald Klein MD, and Barbara Klein MD

Given attributes (which may be discrete or continuous)
and outcomes (Class 1 or Class 0) of a sample of instances,
we develop Smoothing Spline ANOVA methods to estimate the 
*probability* of membership in Class 1, given the attribute 
vector. These methods are suitable when outcomes 
as a function of attributes are not clear-cut, as, for 
example, occurs when estimating risk of some medical outcome, 
given various predictor variables and treatments. 
These methods are penalized log-likelihood methods and 
plots of the cross sections of the estimates are generally
fairly easy to interpret in context. 
We use the results to estimate the probability
of four-year progression of diabetic retinopathy, given the three
predictor variables glycosylated hemoglobin, duration of diabetes and 
body mass index at the study baseline, based on data 
from the Wisconsin Epidemiological Study of Diabetic Retinopathy.
We discuss methods for multiple smoothing parameter selection, 
(the bias-variance tradeoff!!), numerical methods for 
computing the estimate and Bayesian `confidence intervals' 
for the estimate. We discuss methods of informal and formal
model selection (stacked generalization!!) and some open questions.
This work provides further details for work which has previously been 
announced in NIPS-93 and elsewhere.

Other related papers in the same directory include 
gacv.ps.gz, ssanova.ps.gz ml-bib.ps and theses/ywang.thesis.README
 
 Grace Wahba wahba at stat.wisc.edu .....`think snow'