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Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematically studied by exploring available studies of different metaheuristic algorithms used for FS to improve TC. This paper will contribute to the body of existing knowledge by answering four research questions (RQs): 1) What are the different approaches of FS that apply metaheuristic algorithms to improve TC? 2) Does applying metaheuristic algorithms for TC lead to better accuracy than the typical FS methods? 3) How effective are the modified, hybridized metaheuristic algorithms for text FS problems?, and 4) What are the gaps in the current studies and their future directions? These RQs led to a study of recent works on metaheuristic-based FS methods, their contributions, and limitations. Hence, a final list of thirty-seven (37) related articles was extracted and investigated to align with our RQs to generate new knowledge in the domain of study. Most of the conducted papers focused on addressing the TC in tandem with metaheuristic algorithms based on the wrapper and hybrid FS approaches. Future research should focus on using a hybrid-based FS approach as it intuitively handles complex optimization problems and potentiality provide new research opportunities in this rapidly developing field.

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of some of reliability and Hazard estimation methods for Rayleigh logarithmic distribution using simulation with application
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The question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.

In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes

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Publication Date
Sat Apr 24 2021
Journal Name
Turkish Journal Of Computer And Mathematics Education (turcomat)
A Linguistic Study of Epitaphs in Selected English Texts
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This research aims at analysing epitaphs written by Thomas Moore for the memory of Rupert Southey, the epitaph is analysed linguistically and stylistically on four levels graphology, phonology, morphology, and lexico-syntax level to explore the elements that the writer uses the most at each level. Bearing in mind Nowottny approach (1962) (to text analysis) who believes that the linguistic analysis of a literary text is not just a marginal but a necessity” (Bakuuro etal., 2018:34). The researcher has selected and analysed a written epitaph of famous individual associated with English, literature. The study involves both literary and linguistic analysis, with much more concentration through the analysis on the aspect of linguistics. In fact

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Publication Date
Fri Aug 30 2019
Journal Name
Journal Of The College Of Education For Women
A Cognitive Linguistic Study of the English Preposition 'in'
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The present study aims at analyzing the polysemy of the English preposition in from the cognitive linguistic (CL) point of view using Evans' and Tyler's approach (2003). The perplexity faced by Iraqi second language learners (L2) due to the multi-usages of this preposition has motivated the researcher to conduct this study. Seventy-six second year university students participated in this experimental study. The data of the pre-test and post-test were analyzed by SPSS statistical editor. The results have shown the following: First, a progress of more than (0.05≤) has been detected as far as students' understanding of the multiple usages of the preposition in is concerned. Second, the results of the questionnaire have s

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Publication Date
Wed Nov 01 2023
Journal Name
Journal Of Sustainable Studies
A Socio-Pragmatic Study of Insulting in English News
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Media has become a common platform for communication as a tool of offense. English language has many insult words which are commonly used in the world of media. This study investigates the socio-pragmatic aspect of insulting in English news. It aims at identifying and analysing insult words and expressions used by news presenters. To specify the problem of the study, language has a harmful power that hurts the addressees and seriously harm their psychological well-being. The insulting words that are an element of all human languages are the source of this abusive power. The study questions sought to find out are if news presenters use insult words, which insult words, and in what social contexts. In this study, the descriptive method is use

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of Physics: Conference Series
Advanced Machine Learning Models for Banana Sweetness Classification
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

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Publication Date
Fri Jul 01 2011
Journal Name
Alustath
Pun in English and Arabic
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Publication Date
Sat Mar 05 2016
Journal Name
International Journal Of Science And Research (ijsr)
Molecular Docking Studies of Human Ubiquitin Conjugating Enzyme RAD6: A Systematic in Silico Approach
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This study confirms the ubiquitin conjugating enzyme 2B (Rad6) plays a significant role in the DNA repair pathway also because the ubiquitin-conjugating pathway. The DNA repair pathway could be a variety of bypass repair mechanism where the broken base pair is bypassed by permitting the replication fork to labor under the site of injury. This is often done by a shift mechanism wherever deoxyribonucleic acid enzyme - δ is switched with DNA enzyme - η (DNAP - η). Site of DNAP - η is massive enough to permit the broken ester to labor under, and so bypass the broken nucleotide. However, this is often potential solely through the involvement of Proliferating cell nuclear antigen (PCNA) that could be a processivity issue and it acts as a plat

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Publication Date
Wed Jun 01 2022
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
American Standard Code for Information Interchange mapping technique for text hiding in the RGB and gray images
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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Optics And Applications
Modeling and Analysis of a Miniaturized Ring Modulator Using Silicon-Polymer-Metal Hybrid Plasmonic Phase Shifter. Part II: Performance Predictions
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The ring modulator described in part I of this paper is designed here for two operating wavelengths 1550nm and 1310nm. For each wavelength, three structures are designed corresponding to three values of polymer slot widths (40, 50 and 60nm). The performance of these modulators are simulated using COMSOL software (version 4.3b) and the results are discussed and compared with theoretical predictions. The performance of intensity modulation/direct detection short range and long rang optical communication systems incorporating the designed modulators is simulated for 40 and 100Gb/s data rates using Optisystem software (version 12). The results reveal that an average energy per bit as low as 0.05fJ can be obtained when the 1550nm modulator is d

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