A Binary Multi-Objective Chimp Optimizer With Dual Archive for Feature Selection in the Healthcare Domain

Abstract

Medical datasets frequently include vast feature sets with numerous features that are related to one another. As a result, the curse of dimensionality affects learning from a medical dataset to discover significant characteristics, making it necessary to minimize the feature set. Feature selection (FS) is a major step in classification and also in reducing the dimension. This study attempts a novel Binary Multi-objective Chimp Optimization Algorithm (BMOChOA) with dual archive and k-nearest neighbors (KNN) classifier for mining relevant aspects from medical data. In this research, 12 versions of BMOChOA are implemented based on the group information and types of chaotic functions used. The best Pareto front obtained from suggested BMOChOA variations is compared with three benchmark multi-objective FS methods by taking 14 popular medical datasets of variable dimensions. By analyzing the experimental outputs using four multi-objective performance evaluators, it is found that the proposed FS method is superior in finding the best trade-off between the two objective functions: the number of features and classification performance.

Multiclass feature selection with metaheuristic optimization algorithms: a review

“…In future research, this can also be extended to other real-world situations such as the field of technology (spam mail detection, security threat classification) and the industry-customer purchase behavioral prediction, and more, not just to solve medical problems that currently dominate the research endeavors. The future development of heuristic or metaheuristic approaches may tend toward the use of other classifiers popular, creation of more hybrid local search techniques with metaheuristic methods for more accurate prediction as studied in [20,36,60,136], multi-objective binary techniques creation, application to solving medical diagnosis challenges [180], hybridized wrapper-filter approaches are expected to be developed, and more real-world application areas would be embarked upon [184]. models in learning from a meaningful set of data for prediction and solving real-life problems.…”

“…In the following year, Piri et al [ 184 ] proposed a binary multi-objective chimp optimization algorithm (BMOChOA) with dual archive and k-nearest neighbors (KNN) classifier to mine relevant medical data aspects. The study was evaluated using fourteen various dimensions of medical datasets, and the results showed a better performance of the BMOChOA in the features selected and accuracy of performance.…”

An Enhanced Binary Multiobjective Hybrid Filter-Wrapper Chimp Optimization Based Feature Selection Method for COVID-19 Patient Health Prediction

“…At first, the proposed EBMOChOA-FW approach is compared with the existing multi-objective FS methods: MOQB-HHO [19] and BMOChOA [17] based on HHO and ChOA, respectively. MOQBHHO is a multi-objective wrapper-based FS technique that uses quadratic transfer functions to solve the FS challenge in the medical domain.…”

“…As a result, this work offers a binary representation of ChOA that has been built. According to previous studies, this approach has a low feature rating rate, a fast processing rate, and great global and local finding [15,16,17]. To the best of our knowledge, the power of this system for managing the FS mission has yet to be studied.…”

Nature-inspired optimization algorithms and their significance in multi-thresholding image segmentation: an inclusive review

“…al. ( 2021c ) 2021 0 25 Chimp Optimization Algorithm Mathematical and Engineering Optimization problems (Khishe and Mosavi 2020a ; Kaur et al 2021 ; Dhiman 2021 ) Digital Filters (Kaur et al 2021 ), Neural Network (Khishe and Mosavi 2020a ), Hu et al 2021 ), MLT based Image Segmentation (Houssein et al 2021d ), Feature Selection (Wu et al 2021b , Piri et al 2021 ), Image Classification (Annalakshmi and Murugan 2021 ), Electrical Distribution Network (Fathy et al 2021 ), Power System Stabilizer (Aribowo et al 2021b ), Solar Photovoltaic Systems (Nagadurga et al 2021 ), Solar Dish Sterling Power plant (Zayed et al 2021a ), Tunnel FET architecture (Bhattacharya et al 2021 Khishe and Mosavi ( 2020a ) 2020 87 26 Slime Mould Algorithm Mathematical and Engineering Optimization problems (Li et al 2020b ), Yin et al 2022 ), Artificial Neural Network (Zubaidi et al 2020 ), Solar Photovoltaic Systems (Kumar et al 2020 ) (Mostafa et al 2020 Yousri et al 2021 ;El-Fergany 2021a ), Power System Stabilizer (Ekinci et al 2020 ), Servo Systems (Precup et al 2021 ), MLT based Image Segmentation (Liu et al 2021a ; Naik et al 2020 ; Lin et al 2021 ; Zhao et al 2021b ), Image Classification (Wazery et al 2021 ), Feature Selection (Abdel-Basset et al 2021b ), Numerical Optimization (Sun et al 2021b ), Urban Water Resources (Yu et al 2021 ), PEM Fuel Cell Parameter Identification (Gupta et al …”