Accession Number : ADP007141

Title :   Localized Exploratory Projection Pursuit,

Corporate Author : BROWN UNIV PROVIDENCE RI CENTER FOR NEURAL SCIENCE

Personal Author(s) : Intrator, Nathan

Report Date : 1992

Pagination or Media Count : 4

Abstract : Based on CART, we introduce a recursive partitioning method for high dimensional space which partitions the data using low dimensional features. The low dimensional features are extracted via an exploratory projection pursuit (EPP) method, localized to each node in the tree. In addition, we present an exploratory splitting rule that is potentially less biased to the training data. This leads to a nonparametric classifier for high dimensional space that has local feature extractors optimized to different regions in the input space.

Descriptors :   *TRAINING, ADDITION, INPUT, NODES, REGIONS, SPLITTING, TREES, RECURSIVE FUNCTIONS.

Subject Categories : Statistics and Probability
      Information Science

Distribution Statement : APPROVED FOR PUBLIC RELEASE