Open AccessPerformance Enhancement Method for Machine Learning Algorithm
Author(s) -
Archana Chaudhary
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.k7803.0991120
Subject(s) - computer science , machine learning , artificial intelligence , algorithm , android (operating system) , feature selection , online machine learning , active learning (machine learning) , operating system
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 augClassifier 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 augClassifier enhances the performance of Simple Logistics machine learning algorithm.