Weighted λ precision models in rough set data analysis
Ivo Düntsch, Günther Gediga · 2012
We present a parameter free and monotonic alternative to the parametric variable precision model of rough set data analysis, based on the well known PRE index λ of Goodman and Kruskal. Using weighted (parametric) λ models we show how expert knowledge can be integrated without losing the monotonic property of the index. Based on a weighted λ index we present a polynomial algorithm to determine an approximately optimal set of predicting attributes. Finally, we exhibit a connection to Bayesian analysis.