SBAF: A New Activation Function for Artificial Neural Net based Habitability Classification
Machine Learning
2018-06-07 v1 Instrumentation and Methods for Astrophysics
Machine Learning
Abstract
We explore the efficacy of using a novel activation function in Artificial Neural Networks (ANN) in characterizing exoplanets into different classes. We call this Saha-Bora Activation Function (SBAF) as the motivation is derived from long standing understanding of using advanced calculus in modeling habitability score of Exoplanets. The function is demonstrated to possess nice analytical properties and doesn't seem to suffer from local oscillation problems. The manuscript presents the analytical properties of the activation function and the architecture implemented on the function. Keywords: Astroinformatics, Machine Learning, Exoplanets, ANN, Activation Function.
Cite
@article{arxiv.1806.01844,
title = {SBAF: A New Activation Function for Artificial Neural Net based Habitability Classification},
author = {Snehanshu Saha and Archana Mathur and Kakoli Bora and Surbhi Agrawal and Suryoday Basak},
journal= {arXiv preprint arXiv:1806.01844},
year = {2018}
}
Comments
arXiv admin note: substantial text overlap with arXiv:1805.08810