Search Results - (( java implementation mining algorithm ) OR ( program effectiveness selection algorithm ))
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1
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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3
Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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4
Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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5
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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6
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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7
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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8
Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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9
Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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10
A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. The approach is based on optimization of selected test case from test suite T. …”
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11
Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity
Published 2015“…And even though several of the code based addresses procedural programs. Some researchers addressed the issue of test case prioritization using Genetic Algorithm, but the authors do not select modification-revealing before prioritization and used the same fault severity. …”
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12
Automated path testing using the negative selection algorithm
Published 2017“…The proposed algorithm has been applied to the most commonly used benchmarking program which is triangle classifier. …”
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Indexed Article -
13
Some metaheuristic algorithms for solving multiple cross-functional team selection problems
Published 2022“…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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14
Model structure selection for a discrete-time non-linear system using genetic algorithm
Published 2004“…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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A hybrid intelligent algorithm for solving the bilevel programming models
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Working Paper -
16
The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases
Published 2015“…Design-based regression testing approaches have been proposed to address changes at higher levels of abstraction, these approaches may not detect changes in the method body and several of the code based addresses procedural programs. This study presents an optimized regression test case prioritization of selected test cases for object-oriented software using Genetic algorithm with different replacement strategies. …”
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17
Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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18
Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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19
Double-layered hybrid neural network approach for solving mixed integer quadratic bilevel problems
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20
Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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