Title
Adaptive Semi-Supervised Classifier Ensemble for High Dimensional Data Classification.
Abstract
High dimensional data classification with very limited labeled training data is a challenging task in the area of data mining. In order to tackle this task, we first propose a feature selection-based semi-supervised classifier ensemble framework (FSCE) to perform high dimensional data classification. Then, we design an adaptive semi-supervised classifier ensemble framework (ASCE) to improve the performance of FSCE. When compared with FSCE, ASCE is characterized by an adaptive feature selection process, an adaptive weighting process (AWP), and an auxiliary training set generation process (ATSGP). The adaptive feature selection process generates a set of compact subspaces based on the selected attributes obtained by the feature selection algorithms, while the AWP associates each basic semi-supervised classifier in the ensemble with a weight value. The ATSGP enlarges the training set with unlabeled samples. In addition, a set of nonparametric tests are adopted to compare multiple semi-supervised classifier ensemble (SSCE)approaches over different datasets. The experiments on 20 high dimensional real-world datasets show that: 1) the two adaptive processes in ASCE are useful for improving the performance of the SSCE approach and 2) ASCE works well on high dimensional datasets with very limited labeled training data, and outperforms most state-of-the-art SSCE approaches.
Year
DOI
Venue
2019
10.1109/TCYB.2017.2761908
IEEE transactions on cybernetics
Keywords
Field
DocType
Feature extraction,Power capacitors,Semisupervised learning,Training,Laplace equations,Robustness
Semi-supervised learning,Pattern recognition,Feature selection,Feature extraction,Artificial intelligence,Classifier (linguistics),Margin classifier,Ensemble learning,Machine learning,Mathematics,Bayes classifier,Quadratic classifier
Journal
Volume
Issue
ISSN
49
2
2168-2275
Citations 
PageRank 
References 
15
0.50
26
Authors
7
Name
Order
Citations
PageRank
Zhiwen Yu12753220.67
Yidong Zhang2905.00
Jane You31885136.93
C. L. Philip Chen44022244.76
Hau-San Wong5100886.89
Guoqiang Han643943.27
Jun Zhang746849.02