|
|
|
|
|
Ognjen Radovic,Srdan Marinkovic,Jelena Radojicic
Credit scoring attracts special attention of financial institutions. In recent years, deep learning methods have been particularly interesting. In this paper, we compare the performance of ensemble deep learning methods based on decision trees with the b...
ver más
|
|
|
|
|
|
|
|
|
|
|
Haoran Liu, Kehui Xu, Bin Li, Ya Han and Guandong Li
Machine learning classifiers have been rarely used for the identification of seafloor sediment types in the rapidly changing dredge pits for coastal restoration. Our study uses multiple machine learning classifiers to identify the sediment types of the C...
ver más
|
|
|
|
|
|
|
|
|
|
|
Gerasim V. Krivovichev and Valentina Yu. Sergeeva
The paper is devoted to the theoretical and numerical analysis of the two-step method, constructed as a modification of Polyak?s heavy ball method with the inclusion of an additional momentum parameter. For the quadratic case, the convergence conditions ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Stanislav Letkovský, Sylvia Jencová and Petra Va?anicová
Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial in...
ver más
|
|
|
|
|
|
|
|
|
|
|
James Oduor Oyoo, Jael Sanyanda Wekesa and Kennedy Odhiambo Ogada
Road traffic collisions are among the world?s critical issues, causing many casualties, deaths, and economic losses, with a disproportionate burden falling on developing countries. Existing research has been conducted to analyze this situation using diff...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sofía Ramos-Pulido, Neil Hernández-Gress and Gabriela Torres-Delgado
Current research on the career satisfaction of graduates limits educational institutions in devising methods to attain high career satisfaction. Thus, this study aims to use data science models to understand and predict career satisfaction based on infor...
ver más
|
|
|
|
|
|
|
|
|
|
|
Florimond De Smedt, Prabin Kayastha and Megh Raj Dhital
Naïve Bayes classification is widely used for landslide susceptibility analysis, especially in the form of weights-of-evidence. However, when significant conditional dependence is present, the probabilities derived from weights-of-evidence are biased, re...
ver más
|
|
|
|
|
|
|
|
|
|
|
Annwesha Banerjee Majumder, Somsubhra Gupta, Dharmpal Singh, Biswaranjan Acharya, Vassilis C. Gerogiannis, Andreas Kanavos and Panagiotis Pintelas
Heart disease is a leading global cause of mortality, demanding early detection for effective and timely medical intervention. In this study, we propose a machine learning-based model for early heart disease prediction. This model is trained on a dataset...
ver más
|
|
|
|
|
|
|
|
|
|
|
Fan Zhang, Baoxin Yuan, Liang Huang, Yuanqiao Wen, Xue Yang, Rongxin Song and Pieter van Gelder
Accurate fishing activity detection from the trajectories of fishing vessels can not only achieve high-precision fishery management but also ensure the reasonable and sustainable development of marine fishery resources. This paper proposes a new method t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Bradley Walters, Sandra Ortega-Martorell, Ivan Olier and Paulo J. G. Lisboa
A lack of transparency in machine learning models can limit their application. We show that analysis of variance (ANOVA) methods extract interpretable predictive models from them. This is possible because ANOVA decompositions represent multivariate funct...
ver más
|
|
|
|
|
|