Search Results - (( data application mining algorithm ) OR ( parameter estimation mining algorithm ))
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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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Article -
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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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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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Monograph -
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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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Thesis -
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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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Clustering algorithm for market-basket analysis : the underlying concept of data mining technology
Published 2003“…The clustering algorithm based on Small Large Ratios, SLR is presented in a manner that helps to understand the concept of data mining technology in marketbasket analysis. …”
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Modifying iEclat algorithm for infrequent patterns mining
Published 2018“…Pattern ruining has been extensively studied in research due to its successful application in several data mining scenarios. Association rules mining is a basic step to determine the correlation between data items based on frequency of occurrence. …”
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Conference or Workshop Item -
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Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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Web Usage Mining for UUM Learning Care Using Association Rules
Published 2004“…The enormous of information on the World Wide Web makes it obvious candidate for data mining research. Application of data mining techniques to the World Wide Web referred as Web mining where this term has been used in three distint ways; Web Content Mining, Web Structure Mining and Web Usage Mining. …”
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Modifying iEclat algo ithm for infrequent patterns mining
Published 2018“…Pattern ruining has been extensively studied in research due to its successful application in several data mining scenarios. Association rules mining is a basic step to determine the correlation between data items based on frequency of occurrence. …”
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Conference or Workshop Item -
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Web usage mining for UUM learning care using association rules
Published 2004“…The enormous content of information on the World Wide Web makes it obvious candidate for data mining research. Application of data milling techniques to the World Wide Web referred as Web mining where this term has been used in three distinct ways; Web Content Mining, Web Structure Mining and Web Usage Mining. …”
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Thesis -
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Final Year Project -
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Comparative study of apriori-variant algorithms
Published 2016“…One of data mining methods is frequent itemset mining that has been implemented in real world applications, such as identifying buying patterns in grocery and online customers’ behavior.Apriori is a classical algorithm in frequent itemset mining, that able to discover large number or itemset with a certain threshold value. …”
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ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository
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Book Chapter
