Search Results - (( program implementation mining algorithm ) OR ( framework implementation mining algorithm ))
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Improving Extreme Programming Framework With Security Concerns For E-Commerce Applications
Published 2024thesis::doctoral thesis -
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Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…The goal of data mining is to find rules that model the world sufficiently well. …”
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Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…The proposed framework has been implemented in the hypothetical restructured power market using the IEEE Reliability Test System. …”
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Improved Boosting Algorithms by Pre-Pruning and Associative Rule Mining on Decision Trees for predicting Obstructive Sleep Apnea
Published 2017“…The improved algorithms were implemented in OSA dataset and UCI online databases for comparisons. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…Machine learning is an implementation of artificial intelligence (Al) that allows systems to learn and build on knowledge without being directly programmed automatically. …”
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Data mining techniques for transformer failure prediction model: A systematic literature review
Published 2023Conference Paper -
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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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Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure
Published 2011“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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10
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The experimental results show that the proposed feature selection framework performed better when compared to other state-of-the-art feature selection algorithms. …”
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A framework for malware identification based on behavior
Published 2012“…The IF-THEN Prediction Rules which is generated using the data mining technique, ID3 Algorithm is used. In the implementation of malware target classification, Structure Level Rules are utilized to classify malware into possible target class. …”
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13
Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure
Published 2014“…The other 40% of the dataset is used to test generated rules. A simple program of C++ is implemented using Microsoft Visual Studio to test generated rules until accuracy of performance is obtained. …”
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis
Published 2016“…However, frequent pattern mining (FPM) using Apriori-like algorithms and support-confidence framework suffers from the myth of rare item problem in nature. …”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…In this research, a hand-written character recognition model are implemented in C++ programming with ability to classify digits 0, 1, 2, and 3. …”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…No previous study has investigated Orange mining tool as visual programming approach in analysing hyperspectral reflectance data, especially in crop disease detection. …”
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Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013“…The objective was to identify and implement the most accurate algorithm for the KPTM dataset and to come up with a good prediction model using decision tree technique. …”
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The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop
Published 2014“…These representatives are subsequently used in the main process of frequent pattern mining. Our designed algorithm had been implemented with the Erlang language, which is the functional programming paradigm with inherent support for pattern matching. …”
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