Search Results - (( java implementation learning algorithm ) OR ( pattern solution clustering algorithm ))

Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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Comparison between Market Basket Analysis and Partition Around Medoids clustering for knowledge discovering in consumer consumption pattern / Mohammad Adha Ruslan, Nurul Shahira Mo... by Ruslan, Mohammad Adha, Mohammad Ramly, Nurul Shahira, Saberi, Nor Hasliza

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Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data by Laxmi Lydia E., Sharmili N., Nguyen P.T., Hashim W., Maseleno A.

An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…Data clustering is a data mining technique that discovers hidden patterns by creating groups (clusters) of objects. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

“…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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A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

“…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
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Trajectory pattern mining via clustering based on similarity function for transportation surveillance by Choong, Mei Yeen, Chin, Renee Ka Yin, Yeo Kiam Beng @ Abdul Noor, Teo, Kenneth Tze Kin

“…This grouping task is called as clustering. Each of the clusters formed represents a pattern. …”
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Minimizing the number of stunting prevalence using the euclid algorithm clustering approach by Zarlis, Muhammad, Oktavia, Tanty, Buaton, Relita, Ernawan, Ferda, Andrian, Kevin

“…The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. …”
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A modified π rough k-means algorithm for web page recommendation system by Zidane, Khaled Ali Othman

“…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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A comprehensive 3-phase framework for determining the customer’s product usage in a food supply chain by Mad Ali, Mohd Fahmi, Mohd Ariffin, Mohd Khairol Anuar, Delgoshaei, Aidin, Mustapha, Faizal, Supeni, Eris Elianddy

“…Moreover, the efficiency of the outcomes is evaluated using the Silhouette Coefficient, indicating that the proposed algorithm could provide solutions with a 68% score. …”
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A numerical method for frequent pattern mining by Mustapha, Norwati, Nadimi-Shahraki, Mohammad-Hossein, Mamat, Ali, Sulaiman, Md. Nasir

“…A reasonable solution is identifying maximal frequent patterns which form the smallest representative set of patterns to generate all frequent patterns. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

“…Next the problem of data classification is studied as a problem of global, non-smooth and non-convex optimization; this approach consists of describing clusters for the given training sets. The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

“…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 by Ogunfolajin Maruff , Tunde

“…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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A derivative-free optimization method for solving classification problem by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June

“…Approach: The problem of data classification was studied as a problem of global, nonsmooth and nonconvex optimization; this approach consists of describing clusters for the given training sets. The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…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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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

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Spatial-temporal analysis using two-stage clustering and GIS-based MCDM to identify potential market regions by Ernawati, Kamal Baharin, Safiza Suhana, Kasmin, Fauziah

“…Subsequently, the origin schools' regencies/cities were clustered using the k- prototypes algorithm based on their time-series pattern category, the consistency in sending students, average cumulative grade point average (CGPA), and dropout (DO) rate. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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Profiling network traffic of Sultan Idris Shah building (BSIS) using data mining technique / Rusmawati Ishak by Ishak, Rusmawati

“…Orange is a tool that being used in implementing K-Means Clustering Algorithm that could be seen as the most suitable solution to find a network trend pattern of user accessing the Internet and to produce with profiling network. …”
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