# Discriminant Analysis of Distributional Data viaFractional Programming

arXiv: https://arxiv.org/abs/2010.06941 · HTML: https://mlsanity.com/paper/2010.06941/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Oct 2020.

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

- [Interval Fisher's Discriminant Analysis and Visualisation](https://mlsanity.com/paper/2512.11945/) (2025)

## Abstract (arXiv)

We address classification of distributional data, where units are described by histogram or interval-valued variables. The proposed approach uses a linear discriminant function where distributions or intervals are represented by quantile functions, under specific assumptions. This discriminant function allows defining a score for each unit, in the form of a quantile function, which is used to classify the units in two a priori groups, using the Mallows distance. There is a diversity of application areas for the proposed linear discriminant method. In this work we classify the airline companies operating in NY airports based on air time and arrival/departure delays, using a full year fights.