Search Results - (( _ application ((during algorithm) OR (mining algorithm)) ) OR ( web application bat algorithm ))
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Efficient prime-based method for interactive mining of frequent patterns.
Published 2011“…During the mining process, the mining algorithm reduces the number of candidate patterns and comparisons by using a new candidate set called candidate head set and several efficient pruning techniques. …”
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A web usage mining approach based on LCS algorithm in online predicting recommendation systems
Published 2008“…To provide online prediction efficiently, we advance an architecture for online predicting in Web Usage Mining system and propose a novel approach based on LCS algorithm for classifying user navigation patterns for predicting users' future requests. …”
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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…This research will conduct comparison of hybrid Genetic Algorithm and Bat Algorithm (GA-BA) with Genetic Algorithm (GA) and Bat Algorithm (BA). …”
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Academic Exercise -
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Prime-based method for interactive mining of frequent patterns
Published 2010“…Moreover, this study introduces a mining algorithm called PC-miner to mine the mining model frequently with various values of minsup. …”
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Classification of liver disease diagnosis: a comparative study
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An association rule mining approach in predicting flood areas
Published 2017“…This study focuses on the application of Association rules mining for the flood data in Terengganu. …”
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
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An Association Rule Mining Approach in Predicting Flood Areas
Published 2016“…This study focuses on the application of Association rules mining for the flood data in Terengganu. …”
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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification
Published 2014“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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An adaptive anomaly threshold in artificial dendrite cell algorithm
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Profiling network traffic of Sultan Idris Shah building (BSIS) using data mining technique / Rusmawati Ishak
Published 2018“…Based on the trend shows more activities done during the holiday and the attacking activity also frequently happen during the weekend or public holiday. …”
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Modeling forest fires risk using spatial decision tree
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Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection
Published 2024“…This study examines the optimization of Indonesian text sentiment analysis through the integration of feature selection using a genetic algorithm (GA) with deep learning models. The application of GA for data dimensionality reduction from 41,140 to 20,769 features, coupled with fitness evaluation based on SVM, resulted in an observed increase in accuracy by 8.10% for SVM, 36.1% for Naïve Bayes, 7.82% for LSTM, 5.47% for DNN, and 6.25% for CNN. …”
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