Search Results - (( model evaluation based algorithm ) OR ( label classification mining algorithm ))
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Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart...
Published 2023“…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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Thesis -
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Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer
Published 2023“…Machine learning and deep neural networks have shown promise in accurately representing and classifying sentiment, but they require large amounts of labeled data to train the models. In this context, the proposed novel strategy aims to eliminate the need for human labeling of the idiomatic lexicon and fine-tuning the classifier to handle the sentiment classification of tweets containing idiomatic expressions. …”
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Final Year Project / Dissertation / Thesis -
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…In the second part of the study, a novel classification algorithm called Hessian semi-supervised ELM (HSS-ELM) is proposed to enhance the semi-supervised learning of ELM. …”
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5
Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling
Published 2011“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. The K-means is a modified version of the standard K-means by initializing the value K from the value obtained after data mining using Fuzzy-ART and SNC labeling technique. …”
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Article -
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Feature Selection with Harmony Search for Classification: A Review
Published 2021“…A good classification accuracy can be achieved when the model correctly predicted the class labels. …”
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Proceeding -
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Cluster and classification analysis are very interesting data mining topics that can be applied in many fields. …”
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8
Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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9
Predicting game-induced emotions using EEG, data mining and machine learning
Published 2024“…The 20 experiment cases’ results from subject-based experiments supported that the SVM classifer could accurately classify the 4 emotion states with a kappa value over 0.62, demonstrating the SVM-based algorithm’s capabilities in precisely determining the emotion label for each participant’s EEG features’ instance. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction
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Proceeding Paper -
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Incorporating the range-based method into GridSim for modeling task and resource heterogeneity
Published 2017“…As heterogeneity is one of the unique characteristics of Grid computing, which induces additional challenges in designing heuristic-based scheduling algorithms, the main concern when performing simulation experiments for evaluating the performance of scheduling algorithms is how to model and simulate different Grid scheduling scenarios or cases that capture the inherent nature of heterogeneity of Grid computing environment. …”
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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…In this paper, a new cue-based model for dialogue act recognition is presented. …”
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Agent-based extraction algorithm for computational problem solving
Published 2015“…Four agents have been proposed as an agent based model for CPS, which are User_Agent, PAC_Agent, IPO_Agent and Algorithm_Agent. …”
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Thesis -
16
Dingle's Model-based EEG Peak Detection using a Rule-based Classifier
Published 2015“…In this study, the performances of four different peak models of time domain approach which are Dumpala's, Acir's, Liu's, and Dingle's peak models are evaluated for electroencephalogram (EEG) signal peak detection algorithm. …”
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Conference or Workshop Item -
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This comparison is taken as a performance benchmark for the given problem. Finally, a GA based BPNN called (GA-BPNN) is designed and evaluated. …”
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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“…In addition, four types of intrusion detection evaluation datasets were applied to evaluate the proposed model in comparison to the others. …”
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An automatic grading model for semantic complexity of english texts using bidirectional attention-based autoencoder
Published 2024“…The aim of this study is to accurately evaluate the semantic complexity of English text through an autoencoder structure based on bidirectional attention. …”
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