Applying supervised machine learning algorithms and ensemble models to enhance credit card fraud detection. [PDF]
Front Artif IntellAl-Bulushi A, Shaikh AK, Adhikari N.
europepmc +1 more source
Minority Over-Sampling via Entangled-Feature Disentanglement SMOTE (EFD-SMOTE)
Imbalanced data classification remains a critical challenge in the fields of machine learning and data mining. Conventional minority over-sampling techniques, such as SMOTE, primarily synthesize new samples through linear interpolation in the original feature space.
openaire +2 more sources
Global Policy, EarlyView.ABSTRACT Despite the large reappraisal of the EU's security and economic interests in Central Asia, its foreign policy impact has remained weak. This article develops a constructivist, multi‐level framework to examine how European and Chinese approaches to decarbonization are translated into policy in Kazakhstan and Uzbekistan.
Morena Skalamera
wiley +1 more source
Addiction, EarlyView.Abstract Background and aims The market for new psychoactive substances (NPS) is highly dynamic, with hundreds of substances emerging on the European drug market in the last decade. 3‐methylmethcathinone (3‐MMC), a synthetic cathinone and isomer of mephedrone (4‐MMC), gained popularity in the Netherlands due to its psychostimulant effects and initial ...
Nadia Robert Petronella Wilhelmina Hutten +4 more
wiley +1 more source
Explainable deep learning for healthcare workforce attrition: a methodological study on the Watson healthcare synthetic benchmark. [PDF]
Front Public HealthYin D, Lu X, Mei T.
europepmc +1 more source
SC-SMOTE: Stability-constrained SMOTE Based on Multi-model Consistency Constraints
Class imbalance is a prevalent and challenging issue in machine learning that severely degrades the performance of standard classifiers. Although the Synthetic Minority Over-sampling Technique (SMOTE) is widely used to address this problem by interpolating new data points, its standard formulation tends to blindly generate synthetic samples based ...
openaire +1 more source
Asia-Pacific Journal of Financial Studies, EarlyView.Abstract This study develops an explainable machine learning model to predict cryptocurrency delistings using Binance data. It combines quantitative indicators (price, volume) with qualitative data from real‐time news and Reddit. Latent Dirichlet Allocation (LDA) is used to extract topic trends and community reactions, which are transformed into time ...
Sungju Yang, Hunyeong Kwon
wiley +1 more source
Explainable Machine Learning-Based Overall Survival Classification in Prostate Adenocarcinoma Using Integrated Clinical and Transcriptomic Features. [PDF]
Diagnostics (Basel)Kurt HA +2 more
europepmc +1 more source
The nation‐state, non‐Western empires, and the politics of cultural difference
American Journal of Political Science, EarlyView.Abstract While empires have been central to political theory, they almost always refer to Western forms of imperialism and colonialism to which non‐Western societies are subject. But precolonial empires have ruled much of the world for much of known history. Building on recent International Relations (IR) scholarship, this article reconstructs an ideal
Loubna El Amine
wiley +1 more source
Interpretable Machine Learning for Predicting Metabolic Syndrome-Kidney Stone Disease Comorbidity: The Role of Dietary Micronutrients. [PDF]
Food Sci NutrWu G +7 more
europepmc +1 more source