Search Results - (( java implementation mining algorithm ) OR ( using group using 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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Article -
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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Conference or Workshop Item -
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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Final Year Project / Dissertation / Thesis -
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
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…One of the strategies applied is the modified genetic algorithm which relies on, among other things, the separation of the population into groups where each group undergoes mutual recombination operations. …”
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9
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…One of the strategies applied is the modified genetic algorithm which relies on, among other things, the separation of the population into groups where each group undergoes mutual recombination operations. …”
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10
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…One of the strategies applied is the modified genetic algorithm which relies on, among other things, the separation of the population into groups where each group undergoes mutual recombination operations. …”
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11
Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm
Published 2017“…This work is aimed to decrease the total real and reactive power losses while enhancing the voltage profile of the distribution network with less computation time by proposing two new artificial intelligence algorithms, i.e. grouping particle swarm optimization algorithm and grouping genetic algorithm. …”
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12
Classification for large number of variables with two imbalanced groups
Published 2020“…Based on the findings, Algorithm 2 outperforms Algorithm 1 in classifying the minority group, while both proposed algorithms perform equally well in classifying the majority group. …”
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13
Parallel computation of maass cusp forms using mathematica
Published 2013“…To facilitate the complete pullback process of this group, a point locater algorithm is developed. …”
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14
Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar
Published 2016“…Determining the suitable algorithm which can bring the optimized group clusters could be an issue. …”
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15
LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…Empirical studies using these univariate and multivariate models show that the BCD algorithms estimate less irrelevant thresholds compared to the approximation group LASSO algorithms of group least angle regression (GLAR). …”
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UMK Etheses -
16
A method for group formation using genetic algorithm
Published 2010“…However, due to lack of programming skills especially in Java programming language, most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in programming.This paper presents a method for group formation using genetic algorithm, where the members for each group will be generated based on the students’ programming skill.…”
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17
Text spam messages classification using Artificial Immune System (AIS) algorithms
Published 2024thesis::master thesis -
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Group formation using genetic algorithm
Published 2009“…However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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Monograph -
19
Comparison study of sorting techniques in dynamic data structure
Published 2016“…The sorting algorithms were classified into two groups of time complexity, O (n2) group and O(nlog2n) group. …”
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20
Comparison study of sorting techniques in dynamic data structure
Published 2016“…The sorting algorithms were classified into two groups of time complexity, 0 (n2) group and O(nlog2 n) group. …”
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