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

This study embarks on an in-depth analysis of the performance of various kernel functions, namely uniform, epanechnikov, triangular, and gaussian, in window-based and spectral clustering-based models. Employing seven distinct datasets, our approach evaluated both window sizes (25%, 50&...

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Bibliographic Details
Main Authors: Petr Silhavy, Radek Silhavy
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10304119/