Results 61 to 70 of about 2,573 (145)

APAROS: A Clustering-Based Hybrid Approach for Handling Overlapped Regions in Imbalanced Datasets

IEEE Access
In many real-world datasets, the class distribution is often highly imbalanced, and minority class samples are located within the majority regions, leading to significant overlap.
Annam Nandini, Tapas Kumar Mishra, Abinash Pujahari, Sanket Mishra   +3 more
doaj   +1 more source

Impact of data balancing a multiclass dataset before the creation of association rules to study bacterial vaginosis

Intelligent Medicine
Background: Bacterial vaginosis is a polymicrobial syndrome in which the homeostasis exerted by the Latobacillus species that protect the vaginal mucosa has been lost.
Freddy de la Cruz-Ruiz, Juana Canul-Reich, Rafael Rivera-López, Erick de la Cruz-Hernández   +3 more
doaj   +1 more source

Comparison of SMOTE and ADASYN in Optimizing Random Forest Model for Imbalanced Financial Ratio Bankruptcy Prediction

Classification is a data analysis process that can predict classes based on predefined characteristics. In the era of big data, classification can be performed using machine learning.
Fuad Muhajirin Farid, Novanda Rizky Ramadhana, Yeni Rahkmawati   +2 more
core   +1 more source

Improvement of Bank Fraud Detection Through Synthetic Data Generation with Gaussian Noise

Technologies
Bank fraud detection faces critical challenges in imbalanced datasets, where fraudulent transactions are rare, severely impairing model generalization. This study proposes a Gaussian noise-based augmentation method to address class imbalance, contrasting
Fray L. Becerra-Suarez, Halyn Alvarez-Vasquez, Manuel G. Forero   +2 more
doaj   +1 more source

Improving Vehicle Payment Method Classification Using XGBoost with SMOTE and SHAP Interpretation

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Class imbalance in vehicle payment method classification can cause predictive models to become biased toward the majority. This study aims to build a classification model for automotive consumer payment methods using Extreme Gradient Boosting (XGBoost ...
Dedi Trisnawarman, Reza Mahendra
doaj   +1 more source

Predicting coronary artery disease with ensemble-based feature selection and grid search-tuned SVM under class imbalance conditions

Discover Data
Coronary artery disease (CAD) is a common heart condition that leads to numerous deaths. The standard diagnostic tool for CAD, coronary angiography, is expensive, time-consuming, and carries harmful side effects.
Atiyeh Pahlevani, Amirhosein Kashefi, Emrah Arslan, Bulbula Kumeda Kussia, Javad Hassannataj Joloudari   +4 more
doaj   +1 more source

Banking customer churn prediction using random forest based on Smote and Adasyn approach

Tạp chí Phát triển và Hội nhập
Customer Churn is now becoming a significant problem in the banking sector. It is necessary to seek solutions to predict the rate of customer churn in banks; however, the dataset for customer churn prediction in banks is imbalanced.
Cong Thanh Tran
doaj   +1 more source

Analisis Perilaku Remaja Melakukan Seks Pra-Nikah Di Jawa Timur Menggunakan Cart Dengan SMOTE-N-ENN Dan ADASYN-N (Analisis Lanjut SKAP Jawa Timur 2018) [PDF]

, 2020
Pembahasan mengenai seks pra-nikah sering dianggap tabu, padahal efek yang ditimbulkan sangat besar. Di Jawa Timur, angka seks pra-nikah pada 2018 naik 1,4%, yakni dari 0,2% menjadi 1,6% (Badan Kependudukan dan Keluarga Berencana Nasional, 2018).
Wening, Kinanthi Sukma
core  

Macroeconomic indicators and machine learning for financial bubble detection in the Indian stock market

Cogent Economics & Finance
This study investigates financial bubbles in the Indian stock market using the NIFTY 50 index and macroeconomic indicators. Employing the Backward Sup Augmented Dickey–Fuller test, we identified significant bubble occurrences in 2011, 2014, 2016, 2018 ...
Srishty, Muhammed Navas T
doaj   +1 more source

Enhancing Firewall Packet Classification through Artificial Neural Networks and Synthetic Minority Over-Sampling Technique: An Innovative Approach with Evaluative Comparison

Applied Sciences
Firewall packet classification is a critical component of network security, demanding precise and reliable methods to ensure optimal functionality. This study introduces an advanced approach that combines Artificial Neural Networks (ANNs) with various ...
Adem Korkmaz, Selma Bulut, Tarık Talan, Selahattin Kosunalp, Teodor Iliev   +4 more
doaj   +1 more source