Search Results - (( based constructive mining algorithm ) OR ( using optimization model algorithm ))
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Optimization of attribute selection model using bio-inspired algorithms
Published 2019“…Such a finding indicates that bio-inspired algorithms can contribute in identifying the few most important features to be used in data mining model construction.…”
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2
Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…Such a finding indicates that the exploitation of bio-inspired algorithms with ideal combination of wrapper/filtered method can contribute in finding the optimal features to be used in data mining model construction.…”
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3
Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis
Published 2017“…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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4
Portfolio optimization with percentage error-based fuzzy random data for industrial production
Published 2024“…The main objective is to optimize selection based on industrial production, effectively managing uncertainty in traditional portfolio selection models. …”
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Integrated examination and analysis model for improving mobile cloud forensic investigation
Published 2022“…In this context, proposing Forensic Examination and Analysis Methodology using Data mining (FED) and Forensic Examination and analysis methodology using Data mining and Optimization (FEDO) models address these issues. …”
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6
Portfolio optimization with percentage error-based fuzzy random data for industrial production
Published 2024“…The main objective is to optimize selection based on industrial production, effectively managing uncertainty in traditional portfolio selection models. …”
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7
Predicting next page access by Markov models and association rules on web log data
Published 2006“…This algorithm has been used to cluster Web site with similar transition behaviors and compares the transition matrix to an optimal size for efficient used to further improve the efficiency of prediction. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…Many statistical and data mining techniques have been used to predict time series stock market. …”
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A dynamic eLearning prediction modelbased on incomplete activities of eLearning system
Published 2020“…Six data mining algorithms were used in evaluating the model. …”
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A data mining approach to construct graduates employability model in Malaysia
Published 2011“…The performance of Bayes algorithms are also compared against a number of tree-based algorithms. …”
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Prime-based method for interactive mining of frequent patterns
Published 2010“…Then, the proposed method is developed based on the architecture such that the mining model is constructed once, and it can be frequently mined by various minsup. …”
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12
A Data Mining Approach to Construct Graduates Employability Model in Malaysia
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Efficient prime-based method for interactive mining of frequent patterns.
Published 2011“…Our method isolates the mining model from the mining process such that once the mining model is constructed; it can be frequently used by mining process with various minimum support thresholds. …”
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A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…Our algorithm works based on prime factorization, and is called Frequent Pattern-Prime Factorization (FPPF).…”
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15
A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…It then divides the compressed database into a set of conditional databases (a special kind of projected database), each associated with one frequent item or pattern fragment, and mines each such database separately.For a large database, constructing a large tree in the memory is a time consuming task and increase the time of execution.In this paper we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well.Our algorithm works based on prime factorization, and is called Frequent Pattern- Prime Factorization (FPPF).…”
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16
Frequent itemset mining using graph theory / Mohammad Arsyad Mohd Yakop
Published 2017“…The Directed Acyclic Graph in High Dimensional Dataset Mining (DAGHDDM) is a graph-based mining algorithm that represents itemsets in complete graph before FIM takes place. …”
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17
An extended ID3 decision tree algorithm for spatial data
Published 2011“…The objective of this paper is to propose a new spatial decision tree algorithm based on the ID3 algorithm for discrete features represented in points, lines and polygons. …”
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Finding objects with segmentation strategy based multi robot exploration in unknown environment
Published 2013“…Two algorithms were investigated in this paper one is frontier based random search algorithm and the second is efficient algorithm based on segmentation strategy. …”
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Using unique-prime-factorization theorem to mine frequent patterns without generating tree
Published 2011“…Our algorithm works based on prime factorization and is called Prime Factor Miner (PFM). …”
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