Abstract: The purpose of discussed optimal valid partitioning (OVP) methods is uncovering of ordinal or continuous explanatory variables effect on outcome variables of different types. The OVP approach is based on searching partitions of explanatory variables space that in the best way separate observations with different levels of outcomes. Partitions of single variables ranges or two-dimensional admissible areas for pairs of variables are searched inside corresponding families. Statistical validity associated with revealed regularities is estimated with the help of permutation test repeating search of optimal partition for each permuted dataset. Method for output regularities selection is discussed that is based on validity evaluating with the help of two types of permutation tests.

Keywords: Optimal partitioning, statistical validity, permutation test, regularities, explanatory variables effect, complexity

ACM Classification Keywords: H.2.8 Database Applications - Data mining, G.3 Probability and Statistics - Nonparametric statistics, Probabilistic algorithms

Link:

METHODS OF REGULARITIES SEARCHING BASED ON OPTIMAL PARTITIONING

Oleg Senko, Anna Kuznetsova

http://foibg.com/ibs_isc/ibs-08/ibs-08-p20.pdf