GitHub

Oversampling for Imbalanced Learning based on K-Means and SMOTE

K-Means SMOTE is an oversampling method for class-imbalanced data. It aids classification by generating minority class samples in safe and crucial areas of the input space. The method avoids the ...
IEEE

Predicting Stroke Risk Using SMOTE and ROS Machine Learning Techniques

Abstract: The World Stroke Organization has reported that globally 12.2 million people have a stroke for the first time, and 90% of them were related to risk factors that could have been modified.
Scientific Research Publishing

Credit Score Classification Using Advanced Machine Learning: A Comprehensive Approach ()

1 Department of Computer Science, Rutgers University, New Brunswick, NJ, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, NY, USA. This paper presents a ...
IEEE

Text Mining and Emotion Classification on Monkeypox Twitter Dataset: A Deep Learning-Natural Language Processing (NLP) Approach

Abstract: Emotion classification has become a valuable tool in analyzing text and emotions people express in response to events or crises, particularly on social media and other online platforms. The ...
Frontiers

Machine learning approaches to identify Parkinson's disease using voice signal features

Parkinson's Disease (PD) is the second most common age-related neurological disorder that leads to a range of motor and cognitive symptoms. A PD diagnosis is difficult since its symptoms are quite ...