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1
Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…These problems will occur because these fields are mainly used machine learning classifiers. However, machine learning accuracy is affected by the noisy and irrelevant features. …”
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2
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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3
Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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4
Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. This study adopted supervised machine learning algorithm which is the Support Vector Machine (SVM) for classification. …”
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Final Year Project Report / IMRAD -
5
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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6
Impact learning : A learning method from feature’s impact and competition
Published 2023“…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024“…Thus, this study proposed an Opposition-based Learning Binary Bat Algorithm as the feature selection technique in the T-method. …”
Conference Paper -
8
Automated feature selection using boruta algorithm to detect mobile malware
Published 2020“…Boruta algorithm is used to select features automatically for assisting the machine learning. …”
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9
Impact learning: A learning method from feature's impact and competition
Published 2023“…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
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10
Impact learning: A learning method from feature’s impact and competition
Published 2023“…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…The proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. …”
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Performance comparison of feature selection methods for prediction in medical data
Published 2023“…Thus, feature selection should be fully utilized and applied when building machine learning algorithm. …”
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Proceeding Paper -
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Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
Published 2023Conference Paper -
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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15
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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16
Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim
Published 2023“…This study also investigates the significance of data dimension in CCRA: single or multi-dimensional, and the correlation of the features. For the best practice machine learning pipelines, various machine learning models are used to discover the best model for CCRA study. …”
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17
A new SMS spam detection method using both Content-Based and non Content-Based features
Published 2024Conference Paper -
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Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms
Published 2022“…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms
Published 2022“…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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