Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …

Natural Language Processing (NLP) is the computerized approach to analyzing text using
both structured and unstructured data. NLP is a simple, empirically powerful, and reliable …

The ensemble learning method is considered a meaningful yet challenging task. To
enhance the performance of binary classification and predictive analysis, this paper …

Machine learning is a prominent and an intensively studied field in the artificial intelligence
area which assists to enhance the performance of classification. In this paper, the main idea …

Vote-based is one of the ensembles learning methods in which the individual classifier is
situated on numerous weighted categories of the training datasets. In designing a method …

An emergency risk assessment by collecting disaster-affected images via unmanned aerial
vehicles is the current norm. Reasonable rescue planning and resource allocation depend …

An apodized fiber Bragg grating (FBG) is designed to investigate the impacts of side lobe
elimination in quasi-distributed sensing for the estimation of measurands (like temperature …

Serangan malware kian hari kian memprihatinkan. Evolusi malware yang cepat dan
semakin destruktif menimbulkan kekhawatiran bagi banyak pihak. Oleh karena itu, deteksi …

Present dynamic performance reputation and technical innovations in Internet of Things
(IoT) technologies have endowed ultra-inexpensive, energy effcient, smart, and tiny IoT …

Machine learning (ML) is a prominent and extensively researched field in the artificial
intelligence area which assists to strengthen the accomplishment of classification. In this …