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Contrasting and Evaluating Different Clustering Algorithms: A Literature Review

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Τίτλος: Contrasting and Evaluating Different Clustering Algorithms: A Literature Review
Συγγραφείς: Joshi, Swati, Khan, Farhat Ullah, Thakur, Narina
Πηγή: International Journal of Computer Sciences and Engineering; Vol. 2 No. 4 (2014): IJCSE April Edition; 87-91 ; 2347-2693
Στοιχεία εκδότη: IJCSE
Έτος έκδοσης: 2014
Θεματικοί όροι: Clustering, K-Means Algorithm, Hierarchical Clustering Algorithm, K-Medoids Algorithm, Density Based Algorithm
Περιγραφή: Clustering is a practice of splitting data into set of analogous objects; these sets are identified as clusters. Each cluster comprised of points that are alike among them and unalike compared to points of other cluster. This paper is being set to study and put side by side different data clustering algorithms. The algorithms under exploration are: k-means algorithm, hierarchical clustering algorithm, k-medoids algorithm, and density based algorithms. All these algorithms are analyzed on R-tool by taking same data-set under observation.
Τύπος εγγράφου: article in journal/newspaper
Περιγραφή αρχείου: application/pdf
Γλώσσα: English
Relation: https://ijcseonline.org/index.php/j/article/view/106/105; https://ijcseonline.org/index.php/j/article/view/106
Διαθεσιμότητα: https://ijcseonline.org/index.php/j/article/view/106
Rights: https://creativecommons.org/licenses/by/4.0
Αριθμός Καταχώρησης: edsbas.BC8AFB83
Βάση Δεδομένων: BASE
FullText Text:
  Availability: 0
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  – Url: https://ijcseonline.org/index.php/j/article/view/106#
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  Data: Contrasting and Evaluating Different Clustering Algorithms: A Literature Review
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  Data: <searchLink fieldCode="AR" term="%22Joshi%2C+Swati%22">Joshi, Swati</searchLink><br /><searchLink fieldCode="AR" term="%22Khan%2C+Farhat+Ullah%22">Khan, Farhat Ullah</searchLink><br /><searchLink fieldCode="AR" term="%22Thakur%2C+Narina%22">Thakur, Narina</searchLink>
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  Data: International Journal of Computer Sciences and Engineering; Vol. 2 No. 4 (2014): IJCSE April Edition; 87-91 ; 2347-2693
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  Data: IJCSE
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  Data: 2014
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Clustering%22">Clustering</searchLink><br /><searchLink fieldCode="DE" term="%22K-Means+Algorithm%22">K-Means Algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Hierarchical+Clustering+Algorithm%22">Hierarchical Clustering Algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22K-Medoids+Algorithm%22">K-Medoids Algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Density+Based+Algorithm%22">Density Based Algorithm</searchLink>
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  Data: Clustering is a practice of splitting data into set of analogous objects; these sets are identified as clusters. Each cluster comprised of points that are alike among them and unalike compared to points of other cluster. This paper is being set to study and put side by side different data clustering algorithms. The algorithms under exploration are: k-means algorithm, hierarchical clustering algorithm, k-medoids algorithm, and density based algorithms. All these algorithms are analyzed on R-tool by taking same data-set under observation.
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  Data: https://ijcseonline.org/index.php/j/article/view/106/105; https://ijcseonline.org/index.php/j/article/view/106
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      – Text: English
    Subjects:
      – SubjectFull: Clustering
        Type: general
      – SubjectFull: K-Means Algorithm
        Type: general
      – SubjectFull: Hierarchical Clustering Algorithm
        Type: general
      – SubjectFull: K-Medoids Algorithm
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      – SubjectFull: Density Based Algorithm
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              Y: 2014
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            – TitleFull: International Journal of Computer Sciences and Engineering; Vol. 2 No. 4 (2014): IJCSE April Edition
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