Search Results - (( java application mining algorithm ) OR ( using set method algorithm ))
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1
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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2
Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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3
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…These data are processed and stored in appropriate formats in a MySQL server database. 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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4
Mining Sequential Patterns using I-PrefixSpan
Published 2008“…Thus, with I-PrefixSpan there is no in-memory database stored after index set is constructed. The experimental result shows that using Java 2, this method improves the speed of PrefixSpan up to almost two orders of magnitude as well as the memory usage to more than one order of magnitude.…”
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5
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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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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8
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…The third set affirmed that the enhancement on the proposed algorithm, which made use of indexing method that suits the medoids, could boost the performance to about 9 to 27 times in terms of execution time depending on the complexity of the dataset. …”
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9
A new ant based rule extraction algorithm for web classification
Published 2011“…Web documents contain enormous number of attributes as compared to other type of data. Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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10
Logistic regression methods for classification of imbalanced data sets
Published 2012“…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
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11
An Alternative Algorithm for Soft Set Parameter Selection using Special Order
Published 2015“…Comparative analysis were performed between the proposed algorithm and the state-of-the-art parameter reduction algorithm using several soft set in terms of parameter reduction…”
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12
Hybrid bat algorithm for minimum dominating set problem
Published 2017“…This method uses population-based approach called bat algorithm (BA) which explore a wide area of the search space, thus it is capable in the diversification procedure. …”
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13
Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Data pre-processing on the data set may improve the classification results. The methods used were over-sampling, under-sampling and hybrid sampling, which modified the data set class distribution to achieve a better result. …”
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14
Logistic Regression Methods with Truncated Newton Method
Published 2012“…Instead of using IRLS procedure as used by TR-KLR and TR-IRLS, the proposed algorithms implement Newton-Raphson method as the outer algorithm of Truncated Newton for KLR and RLR respectively. …”
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15
A novel solution to traveling salesman problem using fuzzy sets, gravitational search algorithm, and genetic algorithm
Published 2010“…In this approach, suitable fuzzy matrices are used to illustrate the details of the problem. A new optimization algorithm, called the Gravitational Search Algorithm (GSA) is applied to solve TSP as precise as possible, and finally the Genetic Algorithm (GA) finds the final answer in an acceptable amount of time. …”
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16
Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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18
Evaluation of Lightning Current Using Inverse Procedure Algorithm.
Published 2013“…The proposed method can be used for preparing of current data bank that is very useful for considering on lightning effects on the power lines and setting appropriate protection levels on the power systems.…”
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Optimization of attribute selection model using bio-inspired algorithms
Published 2019“…The aim of this paper is to investigate the use of bio-inspired search algorithms in producing optimal attribute set. …”
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Identifying football conflict using soft-set theory in Indonesia super league / Kukuh Wahyudin Pratama
Published 2021“…In managing the conflict situation and identifying the uncertainties, this research proposes a new approach of Computation Intelligence in handling football conflict using Soft Set Theory. Motivated from the fact that every rough set is a soft set, this research derived an alternative algorithm to identify conflict situations from the point of view of soft set theory. …”
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