Classification trees in APL: implementation and application

Authors:
Alexander Skomorokhov;Vladimir Kutinsky
Affiliations:
Institute of Nuclear Power Engineering, Obninsk-5, Kaluga Region, 249020, Russia;Institute of Nuclear Power Engineering, Obninsk-5, Kaluga Region, 249020, Russia
Venue:
Proceedings of the 2001 conference on APL: an arrays odyssey
Year:
2000

Citing 3
Cited 2

Pattern recognition in APL with application to reactor diagnostics

APL '98 Proceedings of the APL98 conference on Array processing language
Pattern Recognition and Neural Networks

Pattern Recognition and Neural Networks
A knowledge discovery method: APL implementation and application

APL '00 Proceedings of the international conference on APL-Berlin-2000 conference

Cooperative computing based on dyalog APL and the R statistical system

ACM SIGAPL APL Quote Quad
Some modifications of the algorithm for construction of classification trees

Pattern Recognition and Image Analysis

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper considers the problem of classification tree based data analysis. Among the topics discussed in the paper are: growing a classification tree using CART style exhaustive search for splits, selecting the right size for the tree using minimal cost-complexity cross-validation pruning, and examples of the application of classification trees.The algorithms are implemented in Dyalog APL.Application example is based on data from vibration monitoring equipment installed on a Nuclear Power Plant in Novovoronehz, Russia and includes classification of vibration spectra of steam generators or coolant pumps and classification of vibration spectra of steam generators of different coolant loops.