MVIBPM: DESIGN OF A MISSING VALUE IDENTIFICATION TECHNIQUE VIA BIOINSPIRED PREDICTIVE MODELING
DOI:
https://doi.org/10.48047/796pj248Keywords:
Missing, Value, NB, kNN, SVM, DF, EHO, Accuracy, Precision, Recall, OptimizationsAbstract
Detecting absent values in time-series data samples is a challenging signal-processing task
that requires pattern analysis, proactive modeling, and regression methods. Researchers propose
various models to optimize the efficiency of missing value identification techniques. Most of them
remain intricate and unsuitable for extensive information sets. Additionally, the limited effectiveness
of basic models when dealing with extensive datasets restricts their applicability for real-time uses. In
order to address these challenges, this article introduces a new Elephant Herding Optimization (EHO)
Model that aims to enhance an effective ensemble classifier for identifying missing values, particularly
suited for feature-based data samples.
Downloads
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
