An adaptive fuzzy k-nearest neighbor method based on parallel particle swarm optimization for bankruptcy prediction

Authors:
Hui-Ling Chen;Da-You Liu;Bo Yang;Jie Liu;Gang Wang;Su-Jing Wang
Affiliations:
Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China;Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China;Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China;Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China;Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China;Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China
Venue:
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Year:
2011

Citing 5
Cited 3

On Comparing Classifiers: Pitfalls toAvoid and a Recommended Approach

Data Mining and Knowledge Discovery
An introduction to ROC analysis

Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)

Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
Predicting bankruptcy using neural networks and other classification methods: The influence of variable selection techniques on model accuracy

Neurocomputing
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients

IEEE Transactions on Evolutionary Computation

An efficient diagnosis system for detection of Parkinson's disease using fuzzy k-nearest neighbor approach

Expert Systems with Applications: An International Journal
Design of an Enhanced Fuzzy k-nearest Neighbor Classifier Based Computer Aided Diagnostic System for Thyroid Disease

Journal of Medical Systems
A nonnegative sparse representation based fuzzy similar neighbor classifier

Neurocomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This study proposes an efficient non-parametric classifier for bankruptcy prediction using an adaptive fuzzy k-nearest neighbor (FKNN) method, where the nearest neighbor k and the fuzzy strength parameter m are adaptively specified by the particle swarm optimization (PSO) approach. In addition to performing the parameter optimization for FKNN, PSO is utilized to choose the most discriminative subset of features for prediction as well. Time varying acceleration coefficients (TVAC) and inertia weight (TVIW) are employed to efficiently control the local and global search ability of PSO. Moreover, both the continuous and binary PSO are implemented in parallel on a multi-core platform. The resultant bankruptcy prediction model, named PTVPSO-FKNN, is compared with three classification methods on a real-world case. The obtained results clearly confirm the superiority of the developed model as compared to the other three methods in terms of Classification accuracy, Type I error, Type II error and AUC (area under the receiver operating characteristic (ROC) curve) criterion. It is also observed that the PTVPSO-FKNN is a powerful feature selection tool which has indentified a subset of best discriminative features. Additionally, the proposed model has gained a great deal of efficiency in terms of CPU time owing to the parallel implementation.