Search Results - (( some applications bayes algorithm ) OR ( its application mining algorithm ))*
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Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim
Published 2024“…The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. …”
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Modifying iEclat algorithm for infrequent patterns mining
Published 2018“…Pattern ruining has been extensively studied in research due to its successful application in several data mining scenarios. …”
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Applying learning to filter text
Published 2005“…Text filtering has been a successful application especially in e-mail filtering. The use of probabilistic approaches such as naïve Bayes algorithm is the effective algorithms currently known for learning to filter or classify text document.Naïve Bayes algorithm is one of the algorithms in Machine Learning that manipulates probability estimation or reasoning about the observed data.The growing of bulk e-mail or known as spam e-mail becomes a threat to users’ privacy and network load and in the case of e -mail filtering,naïve Bayes classifier can be trained to automatically detect spam messages.Similar to the e-mail, forum application may be misused by the user to send bad messages and in some extent may offence other readers.Forum filtering may be less important compared to e-mail spam filtering; however there is a possibility of using naïve Bayes to learn the messages and automatically detect bad messages.Most of the forum application found in the web is applying keyword based text filtering which scan the words and change the detected words into certain representation.Instead of defining a set of keywords to filter the forum messages, this paper will explains the experiment in applying a learning to filter text especially in the educational and anonymous forum message, where there is no user registration required to submit messages.…”
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Modifying iEclat algo ithm for infrequent patterns mining
Published 2018“…Pattern ruining has been extensively studied in research due to its successful application in several data mining scenarios. …”
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Efficient prime-based method for interactive mining of frequent patterns.
Published 2011“…Since rerunning mining algorithms from scratch is very costly and time-consuming, researchers have introduced interactive mining of frequent patterns. …”
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Web Usage Mining Using GSP Algorithm: A Study on Sultanah Bahiyah Library Online Databases
Published 2008“…Application of data mining to the World Wide Web referred as Web mining is at the cross road of research from several research communities which can be divided into three branches: Web Content Mining, Web Structure Mining and Web Usage Mining. …”
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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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Data Classification and Its Application in Credit Card Approval
Published 2004“…The result of this application using the sample credit card approval dataset includes a decision tree, a set of rules derived from the decision tree and its accuracy. …”
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Final Year Project -
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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
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Sequential pattern mining using PrefixSpan with pseudoprojection and separator database
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Evaluation of data mining models for predicting concrete strength
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Final Year Project / Dissertation / Thesis -
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Direct approach for mining association rules from structured XML data
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A comprehensive analysis of blockchain-based cryptocurrency mining impact on energy consumption
Published 2022“…The Proof-of-Work (PoW) algorithm is used for mining ‘Bitcoin’ which is consumed enormous computational power. …”
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