Dissertation/Thesis

Comparison of Various Clustering Algorithms

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Comparison of Various Clustering Algorithms
Συνεισφορές: The Pennsylvania State University CiteSeerX Archives
Πηγή: http://ijcsit.com/docs/Volume+5/vol5issue03/ijcsit2014050387.pdf.
Συλλογή: CiteSeerX
Θεματικοί όροι: Farthest First algorithm, Expectation Maximization algorithm, Density based algorithm, Hierarchical based algorithm, Cobweb algorithm, WEKA tool
Περιγραφή: – A comparative study of clustering algorithms across three different datasets is performed. The algorithms under investigation are partitioning based i.e K-means, Farthest First, Expectation maximization and Non Partitioning based i.e Density based, Hierarchical based and Cobweb. All these algorithms are compared according to the factors size of the dataset, number of clusters and time taken to form clusters. Performance of clustering algorithms are compared using clustering tool WEKA(version 3.7.10).
Τύπος εγγράφου: Thesis
Περιγραφή αρχείου: application/pdf
Γλώσσα: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.661.4971; http://ijcsit.com/docs/Volume+5/vol5issue03/ijcsit2014050387.pdf
Διαθεσιμότητα: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.661.4971
http://ijcsit.com/docs/Volume+5/vol5issue03/ijcsit2014050387.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Αριθμός Καταχώρησης: edsbas.79520D77
Βάση Δεδομένων: BASE
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