Multi-Step Dynamic Ensemble Selection to Estimate Software Effort-Reference-Cited by-同舟云学术

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Multi-Step Dynamic Ensemble Selection to Estimate Software Effort

Published:2024-05-16 Issue:1 Volume:38 Page:
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Jadhav Akshay¹,Shandilya Shishir Kumar²,Izonin Ivan³⁴,Muzyka Roman⁴^ORCID

Affiliation:

1. School of Computer Science and Engineering, Manipal University Jaipur, Jaipur, India

2. School of Data Science and Forecasting, Devi Ahilya Vishwavidyalaya (University), Indore, India

3. School of Engineering, University of Birmingham, Birmingham, UK

4. Department of Artificial Intelligence, Lviv Polytechnic National University, Lviv, Ukraine

Funder

Horizon Europe

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2351718

Reference40 articles.

1. Software Effort Prediction Using Ensemble Learning Methods

2. Hybrid morphological methodology for software development cost estimation

3. LMES: A localized multi-estimator model to estimate software development effort

4. Dynamic selection of classifiers—A comprehensive review

5. Difference between classification and regression in machine learning;Brownlee J.;Machine Learning Mastery,2017

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. SENSE: software effort estimation using novel stacking ensemble learning;Innovations in Systems and Software Engineering;2024-09-14

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