Authors: Adam Bourne
In a stochastic mapping model, a method is described for interpolating un-sampled mapping probabilities given a successive set of observed mappings. The sampled probabilities are calculated from the observed mappings. The previously described method of interpolating values in code space is used to interpolate the un-observed mapping probabilities. The outcomes for subsequent mappings can then be predicted by finding the processes with maximal interpolated probability. Finally, a software package is created and demonstrated to implement the method and tested on a variety of situations for filling in missing element values or categorising data arrays.
Comments: 5 Pages. Demonstration of method has been added to paper
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