Evaluating Kernel Functions in Software Effort Estimation: A Comparative Study of Moving Window and Spectral Clustering Models Across Diverse Datasets-Reference-Cited by-同舟云学术

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Evaluating Kernel Functions in Software Effort Estimation: A Comparative Study of Moving Window and Spectral Clustering Models Across Diverse Datasets

Published:2023 Issue: Volume:11 Page:126335-126351
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Silhavy Petr¹^ORCID,Silhavy Radek¹^ORCID

Affiliation:

1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

Funder

Faculty of Applied Informatics, Tomas Bata University in Zlín

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10304119.pdf?arnumber=10304119

Reference45 articles.

1. Analogy-based software development effort estimation: A systematic mapping and review

2. Algorithmic Optimisation Method for Improving Use Case Points Estimation

3. Robust subspace clustering

4. Improved Effort and Cost Estimation Model Using Artificial Neural Networks and Taguchi Method with Different Activation Functions

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