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