Algorithm learning based neural network integrating feature selection and classification

Hyunsoo Yoon, Cheong Sool Park, Jun Seok Kim, Jun Geol Baek

Research output: Contribution to journalArticle

36 Citations (Scopus)

Abstract

Feature selection and classification techniques have been studied independently without considering the interaction between both procedures, which leads to a degraded performance. In this paper, we present a new neural network approach, which is called an algorithm learning based neural network (ALBNN), to improve classification accuracy by integrating feature selection and classification procedures. In general, a knowledge-based artificial neural network operates on prior knowledge from domain experience, which provides it with better starting points for the target function and leads to better classification accuracy. However, prior knowledge is usually difficult to identify. Instead of using unknown background resources, the proposed method utilizes prior knowledge that is mathematically calculated from the properties of other learning algorithms such as PCA, LARS, C4.5, and SVM. We employ the extreme learning machine in this study to help obtain better initial points faster and avoid irrelevant time-consuming work, such as determining architecture and manual tuning. ALBNN correctly approximates a target hypothesis by both considering the interaction between two procedures and minimizing individual procedure errors. The approach produces new relevant features and improves the classification accuracy. Experimental results exhibit improved performance in various classification problems. ALBNN can be applied to various fields requiring high classification accuracy.

Original languageEnglish
Pages (from-to)231-241
Number of pages11
JournalExpert Systems With Applications
Volume40
Issue number1
DOIs
Publication statusPublished - 2013 Jan

Keywords

  • Algorithm learning based neural network (ALBNN)
  • Classification
  • Extreme learning machine
  • Feature selection
  • Neural network

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Algorithm learning based neural network integrating feature selection and classification'. Together they form a unique fingerprint.

  • Cite this