Optimal Partitioning Statistical Validity Permutation Test Regularities Explanatory Variables Effect Complexity Probability and Statistics Data Mining
Issue Date:
2009
Publisher:
Institute of Information Theories and Applications FOI ITHEA
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.