HGSMAP: a novel heterogeneous graph-based associative percept framework for scenario-based optimal model assignment
Z Qiu, Z Xie, Z Ji, Y Mao, K Cheng - Knowledge and Information Systems, 2024 - Springer
The escalating pervasiveness of big data applications has incited the development of a
multitude of models for the same objectives within the identical scenarios and datasets …
multitude of models for the same objectives within the identical scenarios and datasets …
A Bayesian Framework for Estimating Weibull Distribution Parameters: Applications in Finance, Insurance, and Natural Disaster Analysis
ML Danrimi, H Abubakar - UMYU Journal of …, 2023 - accountingjournal.umyu.edu.ng
This research presents a Bayesian framework for parameter estimation in the two-parameter
Weibull distribution, with applications in finance and investment data analysis. The Weibull …
Weibull distribution, with applications in finance and investment data analysis. The Weibull …
Essays on Model Selection Uncertainty and Model Averaging: Computational and Empirical Work With Beta Regression, Multiple Linear Regression With ARMA …
CZ Allenbrand - 2023 - search.proquest.com
Uncertainty in model selection is under-explored and frequently resolved non-rigorously
through beliefs about generalizability, practical usefulness, and computational ease. This is …
through beliefs about generalizability, practical usefulness, and computational ease. This is …
A Deep Learning Approaches for online shopping Behavior prediction Using Clickstream Data
I Batool - papers.ssrn.com
This research aims to develop a deep learning model using long short-term memory (LSTM)
recurrent neural networks for predicting online user behavior from clickstream data …
recurrent neural networks for predicting online user behavior from clickstream data …