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2009
Springer

The Role of Biomedical Dataset in Classification

9 years 9 months ago
The Role of Biomedical Dataset in Classification
In this paper, we investigate the role of a biomedical dataset on the classification accuracy of an algorithm. We quantify the complexity of a biomedical dataset using five complexity measures: correlation-based feature selection subset merit, noise, imbalance ratio, missing values and information gain. The effect of these complexity measures on classification accuracy is evaluated using five diverse machine learning algorithms: J48 (decision tree), SMO (support vector machines), Naive Bayes (probabilistic), IBk (instance based learner) and JRIP (rule-based induction). The results of our experiments show that noise and correlation-based feature selection subset merit
Ajay Kumar Tanwani, Muddassar Farooq
Added 12 Aug 2010
Updated 12 Aug 2010
Type Conference
Year 2009
Where AIME
Authors Ajay Kumar Tanwani, Muddassar Farooq
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