Imbalanced data preprocessing techniques for machine learning: a systematic mapping study

V Werner de Vargas, JA Schneider Aranda… - … and Information Systems, 2023 - Springer
Abstract Machine Learning (ML) algorithms have been increasingly replacing people in
several application domains—in which the majority suffer from data imbalance. In order to …

A novel XGBoost extension for credit scoring class-imbalanced data combining a generalized extreme value link and a modified focal loss function

J Mushava, M Murray - Expert Systems with Applications, 2022 - Elsevier
There is often a significant class imbalance in credit scoring datasets, mainly in portfolios of
secured loans such as mortgage loans. A class imbalance occurs when the number of non …

[PDF][PDF] Binary classification of rainfall time-series using machine learning algorithms.

S Hudnurkar, N Rayavarapu - International Journal of Electrical & …, 2022 - core.ac.uk
Summer monsoon rainfall contributes more than 75% of the annual rainfall in India. For the
state of Maharashtra, India, this is more than 80% for almost all regions of the state. The high …

Diagnosis of breast cancer on imbalanced dataset using various sampling techniques and machine learning models

R Gupta, R Bhargava… - 2021 14th International …, 2021 - ieeexplore.ieee.org
Breast Cancer is the second most leading cause of death among women. The early
detection of the disease increases the chances of survival of the patient. Therefore, there is …

Cerebral infarction classification using the k-nearest neighbor and naive bayes classifier

SH Rukmawan, FR Aszhari, Z Rustam… - Journal of Physics …, 2021 - iopscience.iop.org
Cerebral infarction is one of the causes of stroke in the brain and is included in ischemic
stroke. To detect infarction in the brain, classification in machine learning can be used. They …

[PDF][PDF] Rice Foreign Object Classification Based on Integrated Color and Textural Feature Using Machine Learning.

A Setiawan, K Adi, CE Widodo - Mathematical Modelling of …, 2023 - researchgate.net
Accepted: 13 March 2023 A blend of natural and artificial foreign objects can be used to
determine the rice quality. The agricultural industry, particularly rice plants, has …

[PDF][PDF] Hepatitis classification using support vector machines and random forest

JE Aurelia, Z Rustam, I Wirasati… - … Journal of Artificial …, 2021 - pdfs.semanticscholar.org
Hepatitis is a medical condition defined by inflammation of the liver. It can be caused by
infection of the liver by hepatitis viruses or is of unknown aetiology. There are 5 main …

A proposed hybrid framework to improve the accuracy of customer churn prediction in telecom industry

S Ouf, KT Mahmoud, MA Abdel-Fattah - Journal of Big Data, 2024 - Springer
In the telecom sector, predicting customer churn has increased in importance in recent
years. Developing a robust and accurate churn prediction model takes time, but it is crucial …

Optimizing predictive precision in imbalanced datasets for actionable revenue change prediction

PD Mahajan, A Maurya, A Megahed, A Elwany… - European Journal of …, 2020 - Elsevier
In business environments where an organization offers contract-based periodic services to
its clients, one crucial task is to predict changes in revenues generated through different …

Cervical cancer classification using convolutional neural network-support vector machine

JE Aurelia, Z Rustam, I Wirasati - … Computing Electronics and …, 2021 - telkomnika.uad.ac.id
Cervical cancer is the second most common cancer in women worldwide, and occurs when
there are presences of abnormal cells in the cervix, which continue to grow uncontrollably. In …