# Distance weighted discrimination of face images for gender classification

arXiv: https://arxiv.org/abs/1706.05029 · HTML: https://mlsanity.com/paper/1706.05029/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jun 2017.

## Built on by (most cited first, 1 of 1)

- [Energy Trees: Regression and Classification With Structured and Mixed-Type Covariates](https://mlsanity.com/paper/2207.04430/) (2022)

## Abstract (arXiv)

We illustrate the advantages of distance weighted discrimination for classification and feature extraction in a High Dimension Low Sample Size (HDLSS) situation. The HDLSS context is a gender classification problem of face images in which the dimension of the data is several orders of magnitude larger than the sample size. We compare distance weighted discrimination with Fisher's linear discriminant, support vector machines, and principal component analysis by exploring their classification interpretation through insightful visuanimations and by examining the classifiers' discriminant errors. This analysis enables us to make new contributions to the understanding of the drivers of human discrimination between males and females.