Search Results - (( java implementation learning algorithm ) OR ( knowledge selection clustering algorithm ))
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The implementation of z-numbers in fuzzy clustering algorithm for wellness of chronic kidney disease patients
Published 2019“…Thus, there are two objectives of this paper; (i) to propose a reliable fuzzy clustering algorithm using z-numbers and; (ii) to cluster the Chronic Kidney Disease (CKD) patients based on the selected indicators to identify which cluster the patients belongs to (Cluster 0, Cluster 1, Cluster 2, Cluster 3 or Cluster 4) based on the membership functions defined. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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An Improved Genetic Clustering Algorithm for Categorical Data
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Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia
Published 2016“…In this study, we utilized Expectation Maximization (EM), K-Means (KM), and Hierarchical Clustering (HC) algorithms to cluster the 38 plantation stocks listed on Bursa Malaysia using 14 financial ratios derived from the fundamental analysis.The clustering allows investors to profile each resulted cluster statistically and assists them in selecting stocks for their stock portfolios rapidly.The performance of each cluster was then assessed using 1-year stock price movement.The result showed that a cluster resulted from EM had a better profile and obtained a higher average capital gain as compared with the other clusters.…”
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A Novel Soft Set Approach in Selecting Clustering Attribute
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Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar
Published 2016“…This unsupervised learning usually leads to undirected knowledge discovery. The cluster detection algorithm searches for clusters of data which are similar to one another by using similarity measures. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Genetic optimisation is responsible for selecting the best parameters of the core clustering to minimise the error. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering
Published 2020“…The framework trains the NN on previously labeled data and its knowledge is used to calculate the error of the core online-offline clustering block. …”
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Centre based evolving clustering framework with extended mobility features for vehicular ad-hoc networks
Published 2021“…The developed CEC-GP also includes an integrated approach that combined all clustering tasks such as cluster formation, cluster head selection, and cluster maintenance. …”
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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 Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective
Published 2013“…Machine learning algorithms are iteration based algorithms, as the new knowledge is based on the previous predicted /calculated knowledge which helps to decrease errors in order to increase efficiency. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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A knowledge based system for automatic classification of web pages
Published 2006“…The paper describes design and implementation of a new knowledge based system for Automatic Information Retrieval DataBase (AIRDB).AIRDB helps the end-user to cluster and classify web pages on the basis of information filtering combined with an Artificial Neural Network (ANN).The classification depends mainly on keyword indexes.A large sample set consists of 11043 web pages of several formats are collected automatically and randomly from various resources.The AIRDB feature selection algorithm is summarized.The feature selection depends upon stemming words of web page. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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