Evolutionary Linear Discriminant Analysis for Multiclass Classification Problems

被引：3
|
作者：
Korns, Michael F. [1 ]
机构：
[1] Lantern Credit LLC, 2240 Village Walk Dr Suite 2305, Henderson, NV 89052 USA
来源：
PROCEEDINGS OF THE 2017 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION (GECCO'17 COMPANION) | 2017年
关键词：
Symbolic Regression and Classification; Genetic Programming; Linear Discriminant Analysis;
D O I：
10.1145/3067695.3075964
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper implements Linear Discriminant Analysis (LDA) together with genetic programming symbolic classification for financial multiclass classification problems. A very brief description of the matrix theory of LDA is included. The implementation details in an industrial strength multiclass classification system are discussed. The algorithm is tested using statistically correct, out of sample training and testing. The algorithm's behavior is demonstrated on real world problems previously published as UCI test suites and financial real world problems.
引用
收藏
页码：233 / 234
页数：2
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