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An extended ID3 decision tree algorithm for spatial data
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A frequent pattern mining algorithm based on FP-growth without generating tree
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A Data Mining Approach to Construct Graduates Employability Model in Malaysia
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An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of applications. …”
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DFP-growth: An efficient algorithm for mining frequent patterns in dynamic database
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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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Thesis -
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014Get full text
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ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository
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Book Chapter -
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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Data Classification and Its Application in Credit Card Approval
Published 2004“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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Final Year Project -
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Classification model for hotspot occurrences using spatial decision tree algorithm
Published 2013“…This study describes the application of data mining technique namely decision tree on forest fires data. …”
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A Scalable Algorithm for Constructing Frequent Pattern Tree
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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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Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data
Published 2016“…Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
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