Maximum Likelihood Estimation and Optimal Coordinates

被引：0

作者：

Spurek, P. ^{[1
]}

Tabor, J. ^{[1
]}

机构：

[1] Jagiellonian Univ, Fac Math & Comp Sci, Lojasiewicza 6, PL-30348 Krakow, Poland

来源：

ADVANCES IN SYSTEMS SCIENCE, ICSS 2016 | 2017年 / 539卷

关键词：

Maximum likelihood estimation; Cross-entropy; Gaussian distribution; INEQUALITY;

D O I：

10.1007/978-3-319-48944-5_1

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We show that the MLE (maximum likelihood estimation) in the class of Gaussian densities can be understood as the search for the best coordinate system which "optimally" underlines the internal structure of the data. This allows in particular to the search for the optimal coordinate system when the origin is fixed in a given point.

引用

页码：3 / 13

页数：11

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