Diabetes is one of the deadliest and costliest diseases. Today, automatic diabetes detection
systems are primarily developed using deep learning (DL) approaches, which give high …

Abstract k NN based ensemble methods minimise the effect of outliers by identifying a set of
data points in the given feature space that are nearest to an unseen observation in order to …

Imbalanced class is a common issue encountered in real-world datasets. Oversampling is a
technique used to tackle imbalanced classes, with the Synthetic Minority Oversampling …

Netflix is a streaming service platform that is growing along with the increasing number of
internet users. This research aims to classify movie and TV show rating datasets on Netflix …

Many smartphones today need to be more precise about choosing one that suits the user's
needs. In fact, smartphone sellers sometimes need help recommending smartphones that …

Data classification methods such as KNN and LMKNN have received extensive attention in
machine learning, but these methods can only perform on complete datasets. However …

Abstract K-Nearest Neighbor (KNN) is a widely used method for both classification and
regression cases. This algorithm, known for its simplicity and effectiveness, relies primarily …

This research is aim to detect kidney cysts from human kidney Ultrasound (USG) 2D Images.
This research uses data from Hospital patients as many as 25 Ultrasound images of the …

Abstract Corona Virus Disease 2019 (covid-19) merupakan pandemi dunia yang
menimbulkan berbagai kerugian di dunia. Diagnosis covid-19 yang valid memerlukan waktu …

Abstract Exploration of Machine Learning methods in the systematic literature shows
successful applications in disease diagnosis, disease prediction, and treatment planning …