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A Hybrid CFS Filter and RF-RFE Wrapper-Based Feature Extraction for Enhanced Agricultural Crop Yield Prediction Modeling

Dhivya Elavarasan, Durai Raj Vincent P M, Kathiravan Srinivasan, Chuan-Yu Chang
2020 Agriculture  
This paper explains a novel hybrid feature extraction procedure, which is an aggregation of the correlation-based filter (CFS) and random forest recursive feature elimination (RFRFE) wrapper framework.  ...  Feature selection can impact a machine learning model's performance by defining a significant feature subset for increasing the performance and identifying the variability.  ...  We also thank the Joint Director of Agriculture, Vellore, Tamil Nadu, India, for providing the details regarding the soil and groundwater properties for the respective village blocks.  ... 
doi:10.3390/agriculture10090400 fatcat:idtjezc7sfgdbdm5lnffxwyosa

A hybrid feature selection method for credit scoring

Sang Ha Van, Nam Nguyen Ha, Hien Nguyen Thi Bao
2017 EAI Endorsed Transactions on Context-aware Systems and Applications  
In this study, we constructed a credit scoring model based on parallel GBM (Gradient Boosted Model), filter and wrapper approaches to evaluate the applicant's credit score from the input features.  ...  The main objective of this paper is to build a hybrid credit scoring model using feature selection approach.  ...  We have introduced a hybrid feature selection approach based on filter and wrapper methods. The accuracy of classifier using the selected features is better than other methods.  ... 
doi:10.4108/eai.6-3-2017.152335 fatcat:6ujjylbee5agth6owgyi4yq7he

A Review of Feature Selection and Classification Approaches for Heart Disease Prediction

Fathania Firwan Firdaus, Hanung Adi Nugroho, Indah Soesanti
2021 IJITEE (International Journal of Information Technology and Electrical Engineering)  
It includes filter, wrapper, embedded, and hybrid. The filter method excels in computation speed. The wrapper and embedded methods consider feature dependencies and interact with classifiers.  ...  Predicting heart disease using a computer-assisted system can reduce time and costs. Feature selection can be used to choose the most relevant variables for heart disease.  ...  There are several feature selection categories, namely filter, wrapper, embedded, and hybrid. A.  ... 
doi:10.22146/ijitee.59193 fatcat:enamvdampvapfhvbwzdufei3tq

Generic Wrapper Based Model using Haralick Features for Silk Fabric Defect Classification

Ms. Shweta Loonkar, NMIMS University Computer Engineering Department, MPSTME, Mumbai-56., Dhirendra S. Mishra, Surya S. Durbha, NMIMS University Computer Engineering Department, MPSTME, Mumbai-56., IIT, Mumbai CSRE, IIT Bombay Powai-76.
2021 Journal of University of Shanghai for Science and Technology  
This paper attempts to experiment and provide such models mainly based on generic wrapper based selection approaches.  ...  Various models based on combination of suitable feature extraction, selection and classification approaches need to be experimented out for the same.  ...  Furthermore, a new paradigm for segmentation and classification uses the wrapper-based approach for feature selection and feature extraction.  ... 
doi:10.51201/jusst/21/11966 fatcat:opptd2qjrrbwza5p2qfmjs7j2i

BFSSGA: Enhancing the Performance of Genetic Algorithm using Boosted Filtering Approach

Shaikh JeeshanKabeer, Moin Mahmud Tanvee, Md Arifur Rahman, Abdul Mottalib, Md. Hasanul Kabir
2012 International Journal of Computer Applications  
paper Boosted Feature Subset Selection (BFSS) which is a boosted t-score filter method, is used as a preprocessing step.  ...  Traditional approaches use a filter based preprocessing step to reduce the dimension of the data on which GA operates and as filtering methods on its own has shown to introduce redundant features, in this  ...  An example is [9] which uses filtering as the preprocessor for partial feature elimination and a Genetic Algorithm (GA) based wrapper model traverses through the remaining features to give the final  ... 
doi:10.5120/8153-1927 fatcat:sxn34ms5mjbxdehbhjegsrv4jy

A two-phase feature selection technique using mutual information and XGB-RFE for credit card fraud detection

C. Victoria Priscilla, D. Padma Prabha
2021 International Journal of Advanced Technology and Engineering Exploration  
Even though effective methods such as data level, algorithm level, hybrid and cost-sensitive learning is proposed by researchers to normalise the imbalanced  ...  De Sá et al. [5] developed a customized classification algorithm that automatically generates the Bayesian network classifier to manage the class imbalance.  ...  Feature selection in ML can be classified as a filter, wrapper and embedded [7] . Filter methods compute the score for each feature and select the feature with the highest score.  ... 
doi:10.19101/ijatee.2021.874615 fatcat:yu7pjby7lvaf5ke2o7uwstpnly

A Hybrid Machine Learning Framework for Predicting Students' Performance in Virtual Learning Environment

Edmund Evangelista
2021 International Journal of Emerging Technologies in Learning (iJET)  
In addition, this study used filter-based and wrapper-based feature selection techniques to select the best features of the dataset related to students' performance.  ...  Consequently, this study proposes a hybrid machine learning framework to predict students' performance using eight classification algorithms and three ensemble methods (Bagging, Boosting, Voting) to determine  ...  An Efficient hybrid filter-wrapper me- taheuristic-based gene selection method for high dimensional datasets.  ... 
doi:10.3991/ijet.v16i24.26151 fatcat:vlw4t55scjhf3ayt2w4eponzw4

Effective Discretization and Hybrid feature selection using Naïve Bayesian classifier for Medical datamining

Ranjit Abraham, Jay B. Simha, S. Sitharama Iyengar
2009 International Journal of Computational Intelligence Research  
Experimental results suggest that on an average the Hybrid Feature Selector gave best results compared to individual techniques with popular filter as well as wrapper based feature selection methods.  ...  The proposed algorithm which is a multi-step process utilizes discretization, filters out irrelevant and least relevant features and finally uses a greedy algorithm such as best first search or wrapper  ...  The reason for using both filter based and wrapper based approach is to reduce the search space in each phase.  ... 
doi:10.5019/j.ijcir.2009.175 fatcat:k6r7ibls2jce3mqmji5a2uuuli

Improving the Performance of Multi-class Intrusion Detection Systems using Feature Reduction [article]

Yasmen Wahba, Ehab ElSalamouny, Ghada ElTaweel
2015 arXiv   pre-print
In this paper we propose a hybrid feature selection method using Correlation-based Feature Selection and Information Gain.  ...  In our work we apply adaptive boosting using na\"ive Bayes as the weak (base) classifier.  ...  Feature selection algorithms are classified into wrapper and filter methods.  ... 
arXiv:1507.06692v1 fatcat:dxayrbvyjrcm3jatmr7op2v65m

Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review

Osamah Mohammed Alyasiri, Yu-N Cheah, Ammar Kamal Abasi, Omar Mustafa Al-Janabi
2022 IEEE Access  
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.  ...  Most of the conducted papers focused on addressing the TC in tandem with metaheuristic algorithms based on the wrapper and hybrid FS approaches.  ...  (LFD) is advised as a filter for feature selection.  ... 
doi:10.1109/access.2022.3165814 fatcat:y3y2jtghxjbtljrl7hdtpw4gvi

Optimization of Multi-objective ENORA and NSGA-II based on Bio-Inspired Algorithms for Classification Problem

Mohammad Aizat Basir
2020 International Journal of Advanced Trends in Computer Science and Engineering  
This discovery implies that the combination of wrapper/filtered method with bio-inspired algorithms can improve the performance of ENORA and NSGA-II for feature selection and classification task.  ...  Selecting optimal feature is very hard to be accomplished, especially for classification task.  ...  ACKNOWLEDGEMENT The authors would like to recognize Universiti Malaysia Terengganu (UMT), Universiti Utara Malaysia (UUM) and Ministry of Education Malaysia (MOE) for the support of services and facilities  ... 
doi:10.30534/ijatcse/2020/1591.32020 fatcat:bay4cea76zbcjfj6yffu67d57q

Bat Algorithm Based Hybrid Filter-Wrapper Approach

Ahmed Majid Taha, Soong-Der Chen, Aida Mustapha
2015 Advances in Operations Research  
This paper presents a new hybrid of Bat Algorithm (BA) based on Mutual Information (MI) and Naive Bayes called BAMI.  ...  The promising features were then used to replace several of the randomly selected features during the search initialization.  ...  Lemma and Hashim [5] proposed a hybrid approach by using boosting technique and integrated some of the features in wrapper methods into a fast filter method.  ... 
doi:10.1155/2015/961494 fatcat:6o7lmpazdvbwhjctusdowd524i

Software Metric and Fault Prediction Using Hybrid FISHER Filter- ANNIGMA Framework

2020 International Journal of Emerging Trends in Engineering Research  
In our paper we used a hybrid algorithm using ANN(Artificial Neural Networks) Wrapper and FISHER Filter techniques.  ...  Testing techniques like alpha-beta testing, Black box testing and White box testing techniques can assure the software quality to a certain level.  ...  The research of previous authors proposed a hybrid wrapper-filter approach for software defect prediction and metric selection.  ... 
doi:10.30534/ijeter/2020/74892020 fatcat:idmk2n3ewbgfxkpntck6g6y4j4

An Efficiency Optimization for Network Intrusion Detection System

Mahmoud M. Sakr, Computer Science Department, Faculty of Computers and Information, Menoufia University, Egypt, Medhat A. Tawfeeq, Ashraf B. El-Sisi
2019 International Journal of Computer Network and Information Security  
In this paper, several feature selection techniques are applied to optimize the efficiency of NIDS. The categories of the applied feature selection techniques are the filter, wrapper and hybrid.  ...  Network intrusion detection systems (NIDS) are designed to monitor and inspect the activities in a network.  ...  under the influence of applying the (wrapper, filter and hybrid) feature selection techniques.  ... 
doi:10.5815/ijcnis.2019.10.01 fatcat:jgbcgjsvtbfcjn3x5iuwe4z2di

A Review of Feature Selection Methods for Machine Learning-Based Disease Risk Prediction

Nicholas Pudjihartono, Tayaza Fadason, Andreas W. Kempa-Liehr, Justin M. O'Sullivan
2022 Frontiers in Bioinformatics  
In this article, we provide a general overview of the different feature selection methods, their advantages, disadvantages, and use cases, focusing on the detection of relevant features (i.e., SNPs) for  ...  Therefore, the generalizability of machine learning models benefits from feature selection, which aims to extract only the most "informative" features and remove noisy "non-informative," irrelevant and  ...  Ghosh et al. (2020) demonstrated that a hybrid filter-wrapper feature selection technique, based on ant colony optimization, performs better than those based solely on filter techniques.  ... 
doi:10.3389/fbinf.2022.927312 fatcat:t2hnwng2cjbvtibevssypequmm
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