Projection-based classification for functional data

被引：5

作者：

Darabi, Nadiyeh ^{[1
]}

Hosseini-Nasab, S. Mohammad E. ^{[1
]}

机构：

[1] Shahid Beheshti Univ, Dept Stat, Tehran, Iran

来源：

STATISTICS | 2020年 / 54卷 / 03期

基金：

美国国家科学基金会;

关键词：

Classification error; Haar basis; modified centroid classifier; projection function; perfect classification; DEPTH-BASED CLASSIFICATION; DISCRIMINATION;

D O I：

10.1080/02331888.2020.1750015

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The classification of functional data has many applications in a variety of problems. A popular method for functional data classification is based on distances of the observations to the class centroid. In this paper, we introduce a weighted version of the centroid classifier that is based on projection functions and can lead to asymptotically perfect classification. We select the projection functions so that they optimize classification performance. The superiority of the proposed method is shown by using a simulation study and two real data sets.

引用

页码：544 / 558

页数：15

共 30 条

[1] Supervised classification for functional data: A weighted distance approach [J].