Devdiscourse

Banks could strengthen credit card fraud screening with ensemble machine learning model

Read more about Banks could strengthen credit card fraud screening with ensemble machine learning model on Devdiscourse ...
Hosted on MSN

AI ensemble models sharpen NBA game predictions and strategy

New research using AI-powered stacked ensemble models has improved accuracy in predicting NBA game results by combining multiple machine learning algorithms. These models not only forecast outcomes ...
IEEE

Prediction of False Data Injection Attacks in Smart Grid using AdaBoost, Deep Learning, and KNN

Abstract: With the advancement and application of computing in electrical infrastructure, all traditional electrical grids are transforming into Smart Grid. Modern Smart Grid are more efficient than ...
Psychology Today

Algorithms and the Erosion of Humanity

Do you remember the early days of social media? The promise of connection, of democratic empowerment, of barriers crumbling and gates opening? In those heady days, the co-founder of Twitter said that ...
GitHub

TreeSHAP-compatible AdaBoost and RUSBoost classifiers for explainable AI on imbalanced datasets.

This package provides custom implementations of AdaBoost and RUSBoost classifiers that are compatible with SHAP's TreeExplainer, enabling fast local explanations for boosting algorithms on imbalanced ...
Nature

Instance Selection and Classification Algorithms in Machine Learning

Instance selection plays a pivotal role in enhancing machine learning by identifying and retaining those data instances that are most informative for the learning process, while discarding redundant ...
Scientific Research Publishing

Sen, P.C., Hajra, M. and Ghosh, M. (2019) Supervised Classification Algorithms in Machine Learning: A Survey and Review. In: Mandal, J.K. and Bhattacharya, D., Eds., Emerging ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
IEEE

Credit Card Fraud Detection using AdaBoost Algorithm in Comparison with Various Machine Learning Algorithms to Measure Accuracy, Sensitivity, Specificity, Precision and F-score

Abstract: Credit card fraud detection is a critical problem for any credit card issuing banks. The AdaBoost classifier is used in this study to identify fraudulent transactions. By comparing the ...
C&EN

Machine Learning Advancements and Strategies in Microplastic and Nanoplastic Detection

Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, People’s Republic of China Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Fudan ...