Making use of the most expressive jumping emerging patterns for classification
type: Item
instance of: scholarly article
title: Making use of the most expressive jumping emerging patterns for classification
zbMATH Open document ID: 0991.68628
DOI: 10.1007/PL00011662
author: Guozhu Dong
author: Kotagiri Ramamohanarao
author: Jinyan (Leo) Li
published in: Knowledge and Information Systems
publication date: 2002-07-25T00:00:00Z
review text: Classification aims to discover a model from training data that can be used to predict the class of test instances. In this paper, we propose the use of jumping emerging patterns (JEPs) as the basis for a new classifier called the JEP-Classifier. Each JEP can capture some crucial difference between a pair of datasets. Then, aggregating all JEPs of large supports can produce a more potent classification power. Procedurally, the JEP-Classifier learns the pair-wise features (sets of JEPs) contained in the training data, and uses the collective impacts contributed by the most expressive pair-wise features to determine the class labels of the test data. Using only the most expressive JEPs in the JEP-Classifier strengthens its resistance to noise in the training data, and reduces its complexity (as there are usually a very large number of JEPs). We use two algorithms for constructing the JEP-Classifier which are both scalable and efficient. These algorithms make use of the border representation to efficiently store and manipulate JEPs. We also present experimental results which show that the JEP-Classifier achieves much higher testing accuracies than the association-based classifier of (Liu et al, 1998), which was reported to outperform C4.5 in general.
Mathematics Subject Classification ID: 68U99
Mathematics Subject Classification ID: 68U35
Mathematics Subject Classification ID: 68T10
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 1771461
zbMATH Keywords: Border-based algorithms
zbMATH Keywords: Border representation
zbMATH Keywords: Classification
zbMATH Keywords: Collective impact
zbMATH Keywords: Most expressive jumping emerging patterns
describes a project that uses: MLC++
describes a project that uses: UCI-ml
describes a project that uses: C4.5
MaRDI profile type: Publication
full work available at URL: pl00011662
OpenAlex ID: W2126146704
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description: scientific article; zbMATH DE number 1771461