Search Results - (( ((program using) OR (problem using)) mining algorithm ) OR ( java application using algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…Having the ability to extract information from XML data would answer the problem of mining the web contents which is a very useful and required power nowadays. …”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…Sequential pattern mining is a new branch of data, mining science that solves inter-transaction pattern mining problems. …”
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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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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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Case Slicing Technique for Feature Selection
Published 2004“…Finding a good classification algorithm is an important component of many data mining projects. …”
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Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm
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Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu
Published 2014“…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
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Research Reports -
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem
Published 2023Conference Paper -
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Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin
Published 2006“…The methods that wilt be applied are conventional statistical methods Markowitz Optimization as well as evolutionary programming (EP) utilizing genetic algorithms. The result of this project are expected to be a comparison of the used methods that will give an indication how well evolutionary programming can perform relative to conventional method and how good the results of the data mining process.…”
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Accelerated mine blast algorithm for ANFIS training for solving classification problems
Published 2016“…Mine Blast Algorithm (MBA) is newly developed metaheuristic technique. …”
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Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip
Published 2023“…This store is facing some problems due to lack of methods predict their sales, so stores can overstock certain products leading to loss to the company, problems like this occur when the management cannot make a budget exact amount. …”
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Student Project -
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Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob
Published 2014“…The objectives of this research are data mining are used to extract useful data from sales and product. …”
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Classification of students' performance in computer programming course according to learning style
Published 2024Conference Paper -
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Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…In rough set approach to data mining, the set of interesting rules are determined using a notion of reduct. …”
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Genetic Algorithm for Web Data Mining
Published 2001“…By doing so, it could assist the process of data mining for information in the World Wide Web. This study used a prototype program based on genetic algorithm to manipulate the initial set of data. …”
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Project Paper Report -
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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