  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.
