Search Results - (( pattern generation mining algorithm ) OR ( evolution optimization modified algorithm ))
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A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. …”
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A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows. …”
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3
A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows.First, it compresses the database representing frequent items into a frequent-pattern tree, or FP-tree, which retains the itemset association information. …”
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4
A numerical method for frequent pattern mining
Published 2009“…Frequent pattern mining is one of the active research themes in data mining. …”
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5
Using unique-prime-factorization theorem to mine frequent patterns without generating tree
Published 2011“…In this study we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well. …”
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The mined frequent patterns are then used in generating association rules. …”
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7
Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset
Published 2018“…The multiple variants in the R-Eclat algorithm generate varied performances in infrequent mining patterns. …”
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8
Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…This modified algorithm called Modified Multi-Objective Particle Swarm Optimization (M-MOPSO) employs a fixed-sized external archive along with a dynamic boundary-based search mechanism to evolve the population. …”
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9
A refined differential evolution algorithm for improving the performance of optimization process
Published 2011“…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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Improved chemotaxis differential evolution optimization algorithm
Published 2015“…The social foraging behavior of Escherichia coli has recently received great attention and it has been employed to solve complex search optimization problems.This paper presents a modified bacterial foraging optimization BFO algorithm, ICDEOA (Improved Chemotaxis Differential Evolution Optimization Algorithm), to cope with premature convergence of reproduction operator.In ICDEOA, reproduction operator of BFOA is replaced with probabilistic reposition operator to enhance the intensification and the diversification of the search space.ICDEOA was compared with state-of-the-art DE and non-DE variants on 7 numerical functions of the 2014 Congress on Evolutionary Computation (CEC 2014). …”
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Direct approach for mining association rules from structured XML data
Published 2012“…The proposed method, XiFLEX has been implemented using two different techniques (java based & XQuery) and compared with the original FLEX algorithm in its basic implementation and the Apriori algorithm for frequent patterns generation. …”
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12
Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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Discovering Pattern in Medical Audiology Data with FP-Growth Algorithm
Published 2012“…We use frequent pattern growth (FP-Growth) algorithm in the data processing step to build the FP-tree data structure and mine it for frequents itemsets. …”
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15
MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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16
Sequential pattern mining on library transaction data
Published 2010“…This paper presents results of the work in applying the sequential pattern mining algorithm namely AprioriAll on a library transaction dataset. …”
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17
Evaluation and optimization of frequent association rule based classification
Published 2014“…Works on sustaining the interestingness of rules generated by data mining algorithms are actively and constantly being examined and developed. …”
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Mining dense data: Association rule discovery on benchmark case study
Published 2016“…In this article, we present comparison result between Apriori and FP-Growth algorithm in generating association rules based on a benchmark data from frequent itemset mining data repository. …”
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Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.]
Published 2024“…The proposed method is based on comparing two algorithms: Apriori and Frequent Pattern Growth (FP- Growth). …”
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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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