# Two novel feature selection algorithms based on crowding distance

arXiv: https://arxiv.org/abs/2105.05212 · HTML: https://mlsanity.com/paper/2105.05212/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 8 references that are in the map.
- First posted on arXiv 11 May 2021.

## Builds on (most cited first, 1 of 1)

- [Relief-Based Feature Selection: Introduction and Review](https://mlsanity.com/paper/1711.08421/) (2017)

## Abstract (arXiv)

In this paper, two novel algorithms for features selection are proposed. The first one is a filter method while the second is wrapper method. Both the proposed algorithms use the crowding distance used in the multiobjective optimization as a metric in order to sort the features. The less crowded features have great effects on the target attribute (class). The experimental results have shown the effectiveness and the robustness of the proposed algorithms.