Improving Accuracy Metric with Precision and Recall Metrics for Optimizing Stochastic Classifier

Hossin, M. and Sulaiman, M.N and Mustapha, N. and Rahmat, R.W (2011) Improving Accuracy Metric with Precision and Recall Metrics for Optimizing Stochastic Classifier. In: Proceedings of the 3rd International Conference on Computing and Informatics, ICOCI 2011, 8-9 June, 2011 Bandung, Indonesia, 2011,8-9 June, Bandung, Indonesia.

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All stochastic classifiers attempt to improve their classifica-tion performance by constructing an optimized classifier. Typically, all of stochastic classification algorithms employ accuracy metric to discriminate an optimal solution. However, the use of accuracy metric could lead the so-lution towards the sub-optimal solution due less discriminating power. Moreover, the accuracy metric also unable to perform optimally when deal-ing with imbalanced class distribution. In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects. We refer the new evaluation metric as optimized accuracy with recall-precision (OARP). This paper demonstrates that the OARP metric is more discriminating than the accuracy metric and able to perform optimally when dealing with imba-lanced class distribution using one simple counter-example. We also dem-onstrate empirically that a naïve stochastic classification algorithm, which is Monte Carlo Sampling (MCS) algorithm trained with the OARP metric, is able to obtain better predictive results than the one trained with the accuracy and F-Measure metrics. Additionally, the t-test analysis also shows a clear advantage of the MCS model trained with the OARP metric over the two se-lected metrics for almost five medical data sets.

Item Type: Proceeding (Paper)
Uncontrolled Keywords: Accuracy Metric, accuracy with recall-precision (OARP),Instance selection (IS), unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: T Technology > T Technology (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development
Depositing User: Karen Kornalius
Date Deposited: 01 Jul 2014 06:45
Last Modified: 04 Jan 2022 06:55

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