Software Effort Estimation using Multi-objective Binary Rao Algorithm

Software Effort Estimation using Multi-objective Binary Rao Algorithm

Software effort estimation depends on the standard of features that are considered. Considering irrelevant features will effect the model by degrading its performance. Most Research studies focus on Single Objective optimization for feature selection. A Multi-Objective Binary Rao Algorithm for Featu...

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Bibliographic Details
Published in:2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT) pp. 1 - 6
Main Authors: Kadali, Sai Vivek, Sahukari, Sai Vamsi, Kalyanam, Vasantha Eswari Devi, Bisi, Manjubala
Format: Conference Proceeding
Language:English
Published: IEEE 06-07-2023
Subjects:
Binary Rao Algorithm
Computational modeling
Deep learning
Estimation
Feature extraction
Feature selection
NSGA-II
Prediction algorithms
Software
Software algorithms
Software development effort estimation
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Summary:Software effort estimation depends on the standard of features that are considered. Considering irrelevant features will effect the model by degrading its performance. Most Research studies focus on Single Objective optimization for feature selection. A Multi-Objective Binary Rao Algorithm for Feature Selection is proposed in this work to estimate software development effort. We have validated the performance of proposed approach using four bench mark datasets and compared with single objective Binary Rao algorithm and NSGA-II algorithm. It is observed that our approach is able to provide better performance than the compared models.
ISSN:2473-7674
DOI:10.1109/ICCCNT56998.2023.10306756