Search Results - (( parameter estimation mining algorithm ) OR ( variable extractions based algorithm ))
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Tree-based contrast subspace mining method
Published 2020“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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Thesis -
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Expectation maximization clustering algorithm for user modeling in web usage mining system
Published 2009“…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…For its fast convergence and for its efficient search procedure, the self-adaptation is proposed in the parameters of the proposed hybrid algorithm. The effectiveness of this algorithm is verified by applying it on the unconstrained and constrained test functions through a simulation study. …”
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Classification for large number of variables with two imbalanced groups
Published 2020“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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Development Of Fall Risk Clustering Algorithm In Older People
Published 2020“…Therefore, the aim of this study is to develop a clustering-based fall risk algorithm which can provide assistances for clinician in management of falls. …”
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Final Year Project / Dissertation / Thesis -
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…If the feature extraction process fails to capture the correct information, the performance or accuracy of the classification algorithm will be negatively impacted. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…In dealing with correlated variables, PCA was embedded in the proposed algorithm. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method
Published 2015“…The purpose of this project is to research more about the flood occurrence in Temerloh, Pahang. The data mining approaches using artificial neural network (ANN) techniques will be use to conduct this research for flood estimation. …”
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Undergraduates Project Papers -
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…This current study proposes an intelligent data mining approach for the Machine Learning- Adaptive Distance Relay (ML-ADR) fault classification model using novel extracted 1-cycle transient voltage and current signals hidden knowledge from both healthy and faulty lines parameters. …”
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Development of an effective clustering algorithm for older fallers
Published 2022“…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. Data from the Malaysian Elders Longitudinal Research (MELoR), comprising 1411 subjects aged ≥55 years, were utilized. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…The textural features extracted are based on the first-order statistics and second-order statistics computed from grey level co-occurrence matrices (GLCM). …”
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Final Year Project -
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Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak
Published 2022“…Waikato Environment for Knowledge Analysis (WEKA) version 3.8 was adopted for data mining analysis at two levels of classification stages. …”
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