Recently, machine learning (ML) has evolved and finds its application in higher education
(HE) for various data analysis. Studies have shown that such an emerging field in …

Heart diseases or the cardiovascular diseases are the main reasons for a large number of
deaths in the world today. Heart disease affects the functioning of blood vessels and can …

The ensemble approach such as boosting is based on heuristic system to develop
prediction paradigms. The ensemble learning techniques are typically more accurate than …

In healthcare system, the predictive modelling procedure for risk estimation of
cardiovascular disease is extremely challenging and an inevitable task. Therefore, the …

With the expanding development of Deep Learning techniques Medical Image Analysis
have become an active field of research. Medical Image Analysis typically refers to the …

In the last decade, there has been an admirable improvement in the classification accuracy
of various machine learning techniques used for disease diagnosis. This even aids in …

This study focuses on comparing the different supervised machine learning classifiers such
as Logistic Regression, Naïve Bayes, Support Vector Machine, K-Nearest Neighbour …

Traditional and ensemble methods are linear models which are considered the most
popular techniques for various learning tasks for the prediction of both nominal and …

Class imbalance is a challenging problem especially in a supervised learning setup, as
most classification algorithms are designed for balanced class distributions. Although …

One of the biggest challenges faced by humanity over time is weather prediction. Rainfall
prediction plays a critical role in agricultural sciences, besides it is pivotal in the prediction of …