Performance Enhancement Method for Machine Learning Algorithm
Archana Chaudhary
Archana Chaudhary*, School of Computer Science & IT, Devi Ahilya University, Khandwa Road, Indore, (Madhya Pradesh), India.
Manuscript received on August 15, 2020. | Revised Manuscript received on August 26, 2020. | Manuscript published on September 10, 2020. | PP: 320-322 | Volume-9 Issue-11, September 2020 | Retrieval Number: 100.1/ijitee.K78030991120 | DOI: 10.35940/ijitee.K7803.0991120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Machine learning is programming computer or a mobile device that learns from experience. Machine learning classification methods are helpful in various fields of Computer Science like driverless cars, product recommendation systems, dynamic pricing, Google translate, online video streaming, internet and mobile fraud detection systems and much more. The present work proposes a method aug Classifier to enhance the performance of Simple Logistics machine learning algorithm. The performance assessment of machine learning algorithm is conducted on a Mobile device using Android Environment. The work also presents the comparative performance investigations of Simple Logistics machine learning algorithm using correlation based feature selection method with respect to performance measures Precision, Sensitivity, F-Measure and ROC. The present work conforms that the aug Classifier enhances the performance of Simple Logistics machine learning algorithm.
Keywords: Classification, Machine learning, Precision, Sensitivity.
Scope of the Article: Machine learning