A Parallel Solver for Generalised Additive Models
An implementation of the backfitting algorithm for generalised additive models which is suitable for parallel computing is described. This implementation is designed to handle large data sets such as those occurring in data mining with several millions of observations on several hundreds of variables. For such large data sets it is crucial to have a fast, parallel implementation for fitting generalised additive models to allow an exploratory analysis of the data within a reasonable time. The...[Show more]
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|Source:||Computational Statistics and Data Analysis|
|01_Hegland_A_Parallel_Solver_for_1999.pdf||405.02 kB||Adobe PDF||Request a copy|
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