Search Results - (( data using optimization algorithm ) OR ( binary classifications learning algorithm ))
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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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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…This paper proposes the integration of feature reduction and data reduction for fuzzy modeling using Cooperative Binary Particle Swarm Optimization (CBPSO). …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…In this study, researcher is trying to improve the clustering of data using an efficient technique via Enhanced Binary Particle Swarm Optimization (EBPSO) as feature selection. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq
Published 2024“…A Convolutional Neural Network (CNN) model was created from scratch for this study. Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Two publicly activity datasets are used; Wireless Sensor Data Mining (WISDM) and Physical Activity Monitoring for Aging People (PAMAP2). …”
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Enhanced extreme learning machine for general regression and classification tasks
Published 2020“…To address this problem, a new approach referred to SVM-ELM is proposed, which utilizes 1-norm support vector machine (SVM) to the hidden layer matrix of ELM in order to automatically discover the optimal number of hidden nodes. The method is developed for regression task by using mean/ median of ELM training errors which is then used as threshold for separating the training data and converting the continuous targets to binary. …”
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network
Published 2022“…Firstly, according to the discreteness of multispectral EEG image features, two-scale convolution kernels were used to calculate and learn useful channel and frequency band feature information in multispectral image data. …”
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Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification
Published 2017“…For example, Binary Particle Search Optimization Common Spatial Pattern (BPSO-CSP) was proposed to choose multiple possible best bands to be used in processing the data. …”
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Performances of machine learning algorithms for binary classification of network anomaly detection system
Published 2018“…The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.…”
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An improved algorithm for iris classification by using support vector machine and binary random machine learning
Published 2018“…The second objective is to conduct a supervised and binary ensemble machine learning technique for classification. …”
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A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
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Analysis Of Personal Protective Equipment Classification Method Using Deep Learning
Published 2022“…Based on the result, CNN algorithm is a good algorithm as the binary classification of PPE achieved high accuracy result.…”
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Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. …”
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Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
Published 2023“…The new Binary Whale Optimization Algorithm is integrated with wrapper feature selection and validated on descriptor selection problem to improve Amphetamine-type stimulants drug classification result. …”
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