Search Results - (( _ application clustering algorithm ) OR ( its application learning algorithm ))
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…Although the swmcan algorithm solves the noise problem in multi-view data, its initial and final graphs are independent and cannot learn from each other. …”
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A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective
Published 2013“…Machine learning algorithms are considered as an efficient way for decision making in computational environments. …”
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Conference or Workshop Item -
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Final Year Project -
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering
Published 2020“…This article presents a prominent framework that integrates each of the NN, a meta-heuristic based on evolutionary genetic algorithm (GA) and a core online-offline clustering (Core). …”
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Modelling kernel methods for unsupervised learning of micro array data
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Monograph -
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Combined generative adversarial network and fuzzy C-means clustering for multi-class voice disorder detection with an imbalanced dataset
Published 2020“…An automatic diagnosis for voice disorders via machine learning algorithms is desired to reduce the cost and time needed for examination by doctors and speech-language pathologists. …”
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A genetic-based HAC technique for parallel clustering of bilingual Malay-English corpora
Published 2012“…Other possible applications include training the algorithm on a hand clustered set of documents, and subsequently applying it to a superset, including unseen documents, incorporating in this way expert knowledge about the domain in the clustering algorithm.…”
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A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…A modified apriori algorithm was employed to reduce the number of clusters effectively on the basis of common data in the clusters of every input to obtain a minimal set of decision rules based on datasets. …”
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Thesis -
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An evolutionary based features construction methods for data summarization approach
Published 2015“…A data summarization approach is proposed due to its capability to learn data stored in multiple tables. …”
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Research Report -
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