English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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

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