Embedded chaotic whale survival algorithm for filter–wrapper feature selection

Classification accuracy provided by a machine learning model depends a lot on the feature set used in the learning process. Feature Selection (FS) is an important and challenging pre-processing technique which helps to identify only the relevant features from a dataset thereby reducing the feature dimension as well as improving the classification accuracy at the same time. The binary version of Whale Optimization Algorithm (WOA) is a popular FS technique which is inspired from the foraging behavior of humpback whales. In this paper, an embedded version of WOA called Embedded Chaotic Whale Survival Algorithm (ECWSA) has been proposed which uses its wrapper process to achieve high classification accuracy and a filter approach to further refine the selected subset with low computation cost. Chaos has been introduced in the ECWSA to guide selection of the type of movement followed by the whales while searching for prey. A fitness-dependent death mechanism has also been introduced in the system of whales which is inspired from the real-life scenario in which whales die if they are unable to catch their prey. The proposed method has been evaluated on 18 well-known UCI datasets and compared with its predecessors as well as some other popular FS methods.

[1]  Rajdeep Chatterjee,et al.  A novel machine learning based feature selection for motor imagery EEG signal classification in Internet of medical things environment , 2019, Future Gener. Comput. Syst..

[2]  Carmelo J. A. Bastos Filho,et al.  A novel binary artificial bee colony algorithm , 2019, Future Gener. Comput. Syst..

[3]  Ruisheng Zhang,et al.  A BPSO-SVM algorithm based on memory renewal and enhanced mutation mechanisms for feature selection , 2017, Appl. Soft Comput..

[4]  Ashraf Darwish,et al.  A New Chaotic Whale Optimization Algorithm for Features Selection , 2018, Journal of Classification.

[5]  Ram Sarkar,et al.  Feature selection for facial emotion recognition using late hill-climbing based memetic algorithm , 2019, Multimedia Tools and Applications.

[6]  Diego Oliva,et al.  Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm , 2017 .

[7]  Xuehua Zhao,et al.  A balanced whale optimization algorithm for constrained engineering design problems , 2019, Applied Mathematical Modelling.

[8]  Ram Sarkar,et al.  A wrapper-filter feature selection technique based on ant colony optimization , 2019, Neural Computing and Applications.

[9]  Kazuyuki Murase,et al.  A new hybrid ant colony optimization algorithm for feature selection , 2012, Expert Syst. Appl..

[10]  Wenhua Zeng,et al.  A New Local Search-Based Multiobjective Optimization Algorithm , 2015, IEEE Transactions on Evolutionary Computation.

[11]  Wlodzislaw Duch,et al.  Feature Selection for High-Dimensional Data - A Pearson Redundancy Based Filter , 2008, Computer Recognition Systems 2.

[12]  Xiaoming Xu,et al.  A hybrid genetic algorithm for feature selection wrapper based on mutual information , 2007, Pattern Recognit. Lett..

[13]  Hiroshi Motoda,et al.  Computational Methods of Feature Selection , 2022 .

[14]  Hossam Faris,et al.  Harris hawks optimization: Algorithm and applications , 2019, Future Gener. Comput. Syst..

[15]  Andrew Lewis,et al.  The Whale Optimization Algorithm , 2016, Adv. Eng. Softw..

[16]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[17]  Isabelle Guyon,et al.  An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..

[18]  Ram Sarkar,et al.  Feature Selection for Facial Emotion Recognition Using Cosine Similarity-Based Harmony Search Algorithm , 2020, Applied Sciences.

[19]  Hossam M. Zawbaa,et al.  Feature selection based on antlion optimization algorithm , 2015, 2015 Third World Conference on Complex Systems (WCCS).

[20]  Simon Laflamme,et al.  Variable input observer for nonstationary high-rate dynamic systems , 2018, Neural Computing and Applications.

[21]  A. Engelbrecht,et al.  A new locally convergent particle swarm optimiser , 2002, IEEE International Conference on Systems, Man and Cybernetics.

[22]  E. Tanyildizi,et al.  Continuous Time Chaotic Systems for Whale Optimization Algorithm , 2018 .

[23]  Zong Woo Geem,et al.  Improved Binary Sailfish Optimizer Based on Adaptive β-Hill Climbing for Feature Selection , 2020, IEEE Access.

[24]  Siddhartha Bhattacharyya,et al.  S-shaped Binary Whale Optimization Algorithm for Feature Selection , 2019 .

[25]  Guanglu Sun,et al.  Feature selection for IoT based on maximal information coefficient , 2018, Future Gener. Comput. Syst..

[26]  João Miguel da Costa Sousa,et al.  Modified binary PSO for feature selection using SVM applied to mortality prediction of septic patients , 2013, Appl. Soft Comput..

[27]  Vivekananda Mukherjee,et al.  Transient Stability Constrained Optimal Power Flow Using Chaotic Whale Optimization Algorithm , 2017 .

[28]  Showmik Bhowmik,et al.  Mutually Informed Correlation Coefficient (MICC) - a New Filter Based Feature Selection Method , 2020, 2020 IEEE Calcutta Conference (CALCON).

[29]  Mita Nasipuri,et al.  A GA based hierarchical feature selection approach for handwritten word recognition , 2019, Neural Computing and Applications.

[30]  Huiling Chen,et al.  Chaotic multi-swarm whale optimizer boosted support vector machine for medical diagnosis , 2020, Appl. Soft Comput..

[31]  Aboul Ella Hassanien,et al.  Binary ant lion approaches for feature selection , 2016, Neurocomputing.

[32]  Ram Sarkar,et al.  Genetic algorithm based cancerous gene identification from microarray data using ensemble of filter methods , 2018, Medical & Biological Engineering & Computing.

[33]  Mita Nasipuri,et al.  Feature Selection for Handwritten Word Recognition Using Memetic Algorithm , 2019 .

[34]  Bodhisattva Dash,et al.  An Improved CAD Framework for Digital Mammogram Classification Using Compound Local Binary Pattern and Chaotic Whale Optimization-Based Kernel Extreme Learning Machine , 2018, ICANN.

[35]  Zahir Tari,et al.  An optimal and stable feature selection approach for traffic classification based on multi-criterion fusion , 2014, Future Gener. Comput. Syst..

[36]  Aboul Ella Hassanien,et al.  Feature selection via a novel chaotic crow search algorithm , 2017, Neural Computing and Applications.

[37]  Majdi M. Mafarja,et al.  Hybrid binary ant lion optimizer with rough set and approximate entropy reducts for feature selection , 2018, Soft Comput..

[38]  Mohsen Ebrahimi Moghaddam,et al.  Bidirectional ant colony optimization for feature selection , 2015, 2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP).

[39]  C. Lakshminarayana,et al.  Optimal siting of capacitors in radial distribution network using Whale Optimization Algorithm , 2017 .

[40]  Ali Kaveh,et al.  Enhanced whale optimization algorithm for sizing optimization of skeletal structures , 2017 .

[41]  Seyed Mohammad Mirjalili,et al.  Whale optimization approaches for wrapper feature selection , 2018, Appl. Soft Comput..

[42]  Ram Sarkar,et al.  Late Acceptance Hill Climbing Based Social Ski Driver Algorithm for Feature Selection , 2020, IEEE Access.

[43]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[44]  Mohammad Ehsan Basiri,et al.  A novel hybrid ACO-GA algorithm for text feature selection , 2009, 2009 IEEE Congress on Evolutionary Computation.

[45]  Ram Sarkar,et al.  Selective Opposition based Grey Wolf Optimization , 2020, Expert Syst. Appl..

[46]  S. Mirjalili,et al.  A new hybrid PSOGSA algorithm for function optimization , 2010, 2010 International Conference on Computer and Information Application.

[47]  Friedhelm Schwenker,et al.  Feature Selection for Recognition of Online Handwritten Bangla Characters , 2019, Neural Processing Letters.

[48]  Mita Nasipuri,et al.  M-HMOGA: A New Multi-Objective Feature Selection Algorithm for Handwritten Numeral Classification , 2019, J. Intell. Syst..

[49]  Millie Pant,et al.  Link based BPSO for feature selection in big data text clustering , 2017, Future Gener. Comput. Syst..

[50]  Li-Yeh Chuang,et al.  Improved binary PSO for feature selection using gene expression data , 2008, Comput. Biol. Chem..

[51]  Sankalap Arora,et al.  Chaotic whale optimization algorithm , 2018, J. Comput. Des. Eng..

[52]  Kazuyuki Murase,et al.  A new local search based hybrid genetic algorithm for feature selection , 2011, Neurocomputing.

[53]  Chun Lu,et al.  An improved GA and a novel PSO-GA-based hybrid algorithm , 2005, Inf. Process. Lett..

[54]  Hossam M. Zawbaa,et al.  Feature selection approach based on whale optimization algorithm , 2017, 2017 Ninth International Conference on Advanced Computational Intelligence (ICACI).

[55]  C. A. Murthy,et al.  Unsupervised Feature Selection Using Feature Similarity , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[56]  Vikrant Bhateja,et al.  Deluge based Genetic Algorithm for feature selection , 2019, Evolutionary Intelligence.

[57]  Said Jadid Abdul Kadir,et al.  Binary Optimization Using Hybrid Grey Wolf Optimization for Feature Selection , 2019, IEEE Access.

[58]  Crina Grosan,et al.  Feature Selection via Chaotic Antlion Optimization , 2016, PloS one.

[59]  Aboul Ella Hassanien,et al.  A binary whale optimization algorithm with hyperbolic tangent fitness function for feature selection , 2017, 2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS).

[60]  Amparo Alonso-Betanzos,et al.  Filter Methods for Feature Selection - A Comparative Study , 2007, IDEAL.

[61]  Majdi M. Mafarja,et al.  Hybrid Whale Optimization Algorithm with simulated annealing for feature selection , 2017, Neurocomputing.

[62]  Ujjwal Maulik,et al.  Recursive Memetic Algorithm for gene selection in microarray data , 2019, Expert Syst. Appl..

[63]  Kavita Burse,et al.  Feature Selection Using Genetic Algorithm and Classification using Weka for Ovarian Cancer , 2016 .

[64]  Mengjie Zhang,et al.  Multi-objective particle swarm optimisation (PSO) for feature selection , 2012, GECCO '12.

[65]  M. Carmen Garrido,et al.  Feature subset selection Filter-Wrapper based on low quality data , 2013, Expert Syst. Appl..

[66]  L. Chuang,et al.  Chaotic maps in binary particle swarm optimization for feature selection , 2008, 2008 IEEE Conference on Soft Computing in Industrial Applications.

[67]  Richard Jensen,et al.  Combining rough and fuzzy sets for feature selection , 2004 .

[68]  Hossam Faris,et al.  Feature Selection Using Salp Swarm Algorithm with Chaos , 2018, ISMSI '18.

[69]  Hossein Nezamabadi-pour,et al.  GSA: A Gravitational Search Algorithm , 2009, Inf. Sci..

[70]  J. S. Wang,et al.  Elman Neural Network Soft-Sensor Model of Conversion Velocity in Polymerization Process Optimized by Chaos Whale Optimization Algorithm , 2017, IEEE Access.

[71]  Ram Rup Sarkar,et al.  Binary Genetic Swarm Optimization: A Combination of GA and PSO for Feature Selection , 2019, J. Intell. Syst..

[72]  Aboul Ella Hassanien,et al.  Chaotic dragonfly algorithm: an improved metaheuristic algorithm for feature selection , 2018, Applied Intelligence.

[73]  Mita Nasipuri,et al.  A clustering‐based feature selection framework for handwritten Indic script classification , 2019, Expert Syst. J. Knowl. Eng..

[74]  Vivekananda Mukherjee,et al.  Application of chaotic whale optimisation algorithm for transient stability constrained optimal power flow , 2017 .

[75]  Vikrant Bhateja,et al.  A histogram based fuzzy ensemble technique for feature selection , 2019, Evolutionary Intelligence.

[76]  Hossam Faris,et al.  Optimizing connection weights in neural networks using the whale optimization algorithm , 2016, Soft Computing.

[77]  Hossein Nezamabadi-pour,et al.  An advanced ACO algorithm for feature subset selection , 2015, Neurocomputing.

[78]  Haibin Zhu,et al.  Fuzzy kNN Text Classifier Based on Gini Index , 2006 .

[79]  Jianzhou Wang,et al.  A novel hybrid system based on a new proposed algorithm-Multi-Objective Whale Optimization Algorithm for wind speed forecasting , 2017 .

[80]  B. Alatas,et al.  Chaos embedded particle swarm optimization algorithms , 2009 .