Search Results - (( java application stemming algorithm ) OR ( structured selection mining 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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Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images
Published 2014“…The high accuracy of object-based classification can be linked to the knowledge discovery produced by the DM algorithm. This algorithm increased the productivity of OBIA, expedited the process of attribute selection, and resulted in an easy-to-use representation of a knowledge model from a decision tree structure.…”
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Medical diagnosis using data mining techniques / Shaiful Nizam Zamri
Published 2003“…The system design part will explains the flow and functionality of the system structure. Then, the system implementation part explains the selected tools chosen for implementing the system which using the Clementine Data Mining Solution. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach
Published 2019“…The top three classification algorithms were selected: IBk, LMT and Random Committee for further classification. …”
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Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis
Published 2017“…Six MVA methods were employed to select the relevant criteria. Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.]
Published 2025“…In this statistical summary procedure, the distribution of attributes and their interactions are crucial for accurately processing the data in accordance with the selected classification or data mining techniques to be performed. …”
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Irrelevant feature and rule removal for structural associative classification
Published 2015“…In the classification task, the presence of irrelevant features can significantly degrade the performance of classification algorithms,in terms of additional processing time, more complex models and the likelihood that the models have poor generalization power due to the over fitting problem.Practical applications of association rule mining often suffer from overwhelming number of rules that are generated, many of which are not interesting or not useful for the application in question.Removing rules comprised of irrelevant features can significantly improve the overall performance.In this paper, we explore and compare the use of a feature selection measure to filter out unnecessary and irrelevant features/attributes prior to association rules generation.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data items.Empirical results confirm that by utilizing feature subset selection prior to association rule generation, a large number of rules with irrelevant features can be eliminated.More importantly, the results reveal that removing rules that hold irrelevant features improve the accuracy rate and capability to retain the rule coverage rate of structural associative association.…”
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…Most text summarization research mainly uses co-selection based analysis to evaluate the summary result. …”
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Multi agent and artificial neural networks prediction framework development for stock investment strategy
Published 2016“…WMA comprises of an algorithm for web mining which enables it to mine and extract semi-structured information and create new structured information using ontology. …”
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Multi-agent and artificial neural networks prediction framework development for stock investment strategy
Published 2016“…WMA comprises of an algorithm for web mining which enables it to mine and extract semi-structured information and create new structured information using ontology. …”
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Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing
Published 2015“…OBIA was performed in a rule-based structure that requires selecting and identifying rules. …”
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A hybrid local search algorithm for minimum dominating set problems
Published 2022“…Compared to the literature, the proposed algorithm outperformed other algorithms in most of the tested instances. …”
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A hybrid local search algorithm for minimum dominating set problems
Published 2022“…Compared to the literature, the proposed algorithm outperformed other algorithms in most of the tested instances. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Classification is an important data mining task with different applications in many fields. …”
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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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Sectoral GDP Convergence of Selected RCEP Countries: Lead or Lags?
Published 2017“…Structural convergence occurs, if income convergence progress is associated with sectoral convergence or disaggregated level. …”
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Application of data mining techniques for economic evaluation of air pollution impact and control
Published 2007“…For that purpose, we use data mining techniques. Data mining techniques applied in this thesis were: 1) Group method of data handling (GMDH), originally from engineering, introducing principles of evolution - inheritance, mutation and selection - for generating a network structure systematically to develop the automatic model, synthesis, and its validation; 2) The weighted least square (WLS) and step wise regression were also applied for some cases; 3) The classification-based association rules were applied. …”
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