Discovering Test Statistics Using Genetic Programming

被引：2

作者：

Moore, Jason H. ^{[1
]}

Olson, Randal S. ^{[1
]}

Chen, Yong ^{[1
]}

Sipper, Moshe ^{[1
,2
]}

机构：

[1] Univ Penn, Inst Biomed Informat, Philadelphia, PA 19104 USA

[2] Ben Gurion Univ Negev, Dept Comp Sci, Beer Sheva, Israel

来源：

PROCEEDINGS OF THE 2019 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION (GECCCO'19 COMPANION) | 2019年

基金：

美国国家卫生研究院;

关键词：

Genetic Programming; Statistics; Optimization; T-Test;

D O I：

10.1145/3319619.3326754

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

We describe a genetic programming-based system for the automated discovery of new test statistics. Specifically, our system was able to discover test statistics as powerful as the t-test for comparing sample means from two distributions with equal variances [1].

引用

页码：29 / 30

页数：2