Search Results - (( basic learning rules algorithm ) OR ( java implementation mining algorithm ))
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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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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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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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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
Web Usage Mining for UUM Learning Care Using Association Rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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Web usage mining for UUM learning care using association rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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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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Comparative study on job scheduling using priority rule and machine learning
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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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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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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…Total rules number, rules length and rules accuracy for the generation rules are recorded. …”
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Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure
Published 2014“…This project proposed a data mining technique called Association Rule Mining. Basically Association Rule Mining is to investigate the rules according to the predefined parameter. …”
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Penggunaan penggugusan subtraktif bagi menjana peraturan kabur
Published 2005“…The second method is by using antecedent multi dimension membership function similar to the fuzzy cluster performed into input area. The basic idea in this paper work is how to learn and generate the optimum rules that required controlling input without decreasing the control quality. …”
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Identification model for hearing loss symptoms using machine learning techniques
Published 2014“…In order to find, the correlation that exist between the hearing thresholds and symptoms of hearing loss, FP-Growth and association rule algorithms were first used to experiment with a small sample and large sample datasets. …”
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Email spam classification based on deep learning methods: A review
Published 2025“…The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…The effect of the training data pool volume in the 2D and 3D parts of this study has also been evaluated, and the sufficient volume for each data type is selected.Furthermore, five common training paradigms, i.e., batch training with weight and bias learning rules, conjugate gradient with Fletcher reverse updates, resilient propagation,gradient descent with momentum and adaptive learning rate and Levenberg-Marquardt with weight and bias learning rules, are compared for both 2D and 3D. …”
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