Research Area:  Metaheuristic Computing
Nowadays machine learning algorithms are applied to various fields but still there is a requirement for improving the accuracy of machine learning algorithms for certain applications. This paper focuses on using Weightless Swarm Algorithm as transformation technique for enhancing the accurateness of machine learning techniques in SONAR dataset classification. Three different machine learning techniques namely Random Forest, Stochastic Gradient Descent, and Decision Tree are examined as classifier for categorizing the SONAR data as either mineral or normal rock. Notably, Mathews correlation Coefficient of Random forest classifier is 75.27% and this is increased to 81.81% through the usage of Weightless Swarm Algorithm as transformation technique.
Keywords:  
machine learning algorithm
accuracy
Weightless Swarm Algorithm
SONAR dataset
Author(s) Name:  Bharanidharan. N, Sai Siva Sasank T, Jeevan Sreeram Reddy, Naga Sujan T
Journal name:  
Conferrence name:  2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)
Publisher name:  IEEE
DOI:  10.1109/ICOEI51242.2021.9453006
Volume Information:  
Paper Link:   https://ieeexplore.ieee.org/abstract/document/9453006