MOANOFS: Multi-Objective Automated Negotiation based Online Feature Selection System for Big Data Classification

TL;DR

This paper introduces MOANOFS, an online feature selection system that combines online learning and automated negotiation to effectively select relevant features in big data classification tasks, especially with sequential data.

Contribution

It proposes a novel multi-objective automated negotiation framework for online feature selection, integrating trust evaluation among multiple learners for improved relevance and accuracy.

Findings

Achieves high classification accuracy on real-world big data applications.

Effectively selects relevant features in sequential data scenarios.

Demonstrates robustness across different domains.

Abstract

Feature Selection (FS) plays an important role in learning and classification tasks. The object of FS is to select the relevant and non-redundant features. Considering the huge amount number of features in real-world applications, FS methods using batch learning technique can't resolve big data problem especially when data arrive sequentially. In this paper, we propose an online feature selection system which resolves this problem. More specifically, we treat the problem of online supervised feature selection for binary classification as a decision-making problem. A philosophical vision to this problem leads to a hybridization between two important domains: feature selection using online learning technique (OFS) and automated negotiation (AN). The proposed OFS system called MOANOFS (Multi-Objective Automated Negotiation based Online Feature Selection) uses two levels of decision. In the first level, from n learners (or OFS methods), we decide which are the k trustful ones (with high confidence or trust value). These elected k learners will participate in the second level. In this level, we integrate our proposed Multilateral Automated Negotiation based OFS (MANOFS) method to decide finally which is the best solution or which are relevant features. We show that MOANOFS system is applicable to different domains successfully and achieves high accuracy with several real-world applications. Index Terms: Feature selection, online learning, multi-objective automated negotiation, trust, classification, big data.