---
title: Improved Crayfish Optimization for Feature Selection
url: https://www.ml-quant.com/papers/repec/gam-jmathe-v-12-y-2024-i-15-p-2364-d-1445421/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:gam:jmathe:v:12:y:2024:i:15:p:2364-:d:1445421
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.mdpi.com%2F2227-7390%2F12%2F15%2F2364%2Fpdf%3Bh%3Drepec%3Agam%3Ajmathe%3Av%3A12%3Ay%3A2024%3Ai%3A15%3Ap%3A2364-%3Ad%3A1445421
featured: 2024-08-07
citations: unknown
topic: ML & AI Methods
---


# Improved Crayfish Optimization for Feature Selection

The newly developed Improved Binary Crayfish Optimization Algorithm (IBCOA) enhances feature selection in data mining and machine learning, thus improving classification accuracy.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.mdpi.com%2F2227-7390%2F12%2F15%2F2364%2Fpdf%3Bh%3Drepec%3Agam%3Ajmathe%3Av%3A12%3Ay%3A2024%3Ai%3A15%3Ap%3A2364-%3Ad%3A1445421
- Identifier: RePEc:gam:jmathe:v:12:y:2024:i:15:p:2364-:d:1445421
- Released: 2024-08-07
- First featured: Quant Letter No. 60 (2024-08-07): https://www.ml-quant.com/issues/2024-08-07/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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