Search Results - (( binary classifications mining algorithm ) OR ( opening classification using algorithm ))
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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An improved algorithm for iris classification by using support vector machine and binary random machine learning
Published 2018“…The first objective of this study is to improve a new algorithm technique for classification. The new algorithm come from a combination of an ideas of k-NN algorithm and ensemble concept. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…The proposed method is applied to 14 real world dataset from the machine learning repository. The algorithm’s performance is illustrated by the corresponding table of the classification rate. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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Named entity recognition using a new fuzzy support vector machine.
Published 2008“…The design of our method is a kind of One-Against-All multi classification technique to solve the traditional binary classifier in SVM.…”
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Development of I-Complain@META: a complaint management system for FKMT students using naive bayes classification algorithm
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Enhancement of new smooth support vector machines for classification problems
Published 2011“…Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in data mining. …”
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Detecting canopy openings in logged-over forests: a multi-classifier analysis of PlanetScope imagery
Published 2024“…Three different classification algorithms, namely maximum likelihood classifier (MLC), support vector machine (SVM) and object-based image analysis (OBIA) were used and compared to identify canopy opening areas. …”
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Waste management using machine learning and deep learning algorithms
Published 2020“…The model that we have used are the classification models. For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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Overview of biomedical relations extraction using hybrid rule-based approaches.
Published 2013“…These huge amounts of information cause very difficult task of extraction or classification.Therefore, there is a need for knowledge discovery and text mining tools in this field. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis
Published 2022“…Therefore, a model called Multi-Tasking Learning based on Convolutional Hierarchical Attention Neural Network (MTL-CHAN) is proposed, comprising of (i) shared word encoder and word attention networks across classification tasks, (ii) task-specific layers with convolutional neural network-based attention (CNNA) on sentence-level; to handle the Arabic explicit negation words and improve the classification performance by training Arabic classification tasks (binary, ternary, and five) jointly. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing
Published 2014“…This research concerns on binary classification which is classified into two classes. …”
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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons
Published 2020“…However, the problem of improving the accuracy and efficiency of classification models remains open and yet to be resolved. …”
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