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Title: :  Clustering Method for Mixed Categorical and Numerical Data
PaperId: :  2501
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 2 Issue 3 2016
DUI:    16.0415/IJARIIE-2501
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
PRAJAPATI MADHAVIgovernment engineering college,sector 28, gandhinagar
J.S. DHOBIgovernment engineering college,sector 28, gandhinagar

Abstract

computer engineering
Mixed data clustering, Entropy based clustering, data mining
Clustering is the process of discovering a set of categories to which objects should be assigned. A cluster is comprised of a number of similar objects collected or grouped together. The current requirements to cluster real world data sets are scalability, ability to handle any kind of data like categorical and numerical. Traditional algorithm can cluster categorical or numerical data but not the both. Various clustering algorithms have been developed to group data into clusters. However, these clustering algorithms work effectively either on pure numeric data or on pure categorical data, most of them perform poorly on mixed categorical and numerical data types in previous k-means algorithm was used but it is not accurate for large datasets. This study includes the discussion about the different clustering algorithm, its advantages and limitations. An efficient method is proposed for clustering both numerical and categorical data.

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IJARIIE PRAJAPATI MADHAVI, and J.S. DHOBI. "Clustering Method for Mixed Categorical and Numerical Data" International Journal Of Advance Research And Innovative Ideas In Education Volume 2 Issue 3 2016 Page 3828-3836
MLA PRAJAPATI MADHAVI, and J.S. DHOBI. "Clustering Method for Mixed Categorical and Numerical Data." International Journal Of Advance Research And Innovative Ideas In Education 2.3(2016) : 3828-3836.
APA PRAJAPATI MADHAVI, & J.S. DHOBI. (2016). Clustering Method for Mixed Categorical and Numerical Data. International Journal Of Advance Research And Innovative Ideas In Education, 2(3), 3828-3836.
Chicago PRAJAPATI MADHAVI, and J.S. DHOBI. "Clustering Method for Mixed Categorical and Numerical Data." International Journal Of Advance Research And Innovative Ideas In Education 2, no. 3 (2016) : 3828-3836.
Oxford PRAJAPATI MADHAVI, and J.S. DHOBI. 'Clustering Method for Mixed Categorical and Numerical Data', International Journal Of Advance Research And Innovative Ideas In Education, vol. 2, no. 3, 2016, p. 3828-3836. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Clustering_Method_for_Mixed_Categorical_and_Numerical_Data_ijariie2501.pdf (Accessed : ).
Harvard PRAJAPATI MADHAVI, and J.S. DHOBI. (2016) 'Clustering Method for Mixed Categorical and Numerical Data', International Journal Of Advance Research And Innovative Ideas In Education, 2(3), pp. 3828-3836IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Clustering_Method_for_Mixed_Categorical_and_Numerical_Data_ijariie2501.pdf (Accessed : )
IEEE PRAJAPATI MADHAVI, and J.S. DHOBI, "Clustering Method for Mixed Categorical and Numerical Data," International Journal Of Advance Research And Innovative Ideas In Education, vol. 2, no. 3, pp. 3828-3836, May-Jun 2016. [Online]. Available: https://ijariie.com/AdminUploadPdf/Clustering_Method_for_Mixed_Categorical_and_Numerical_Data_ijariie2501.pdf [Accessed : ].
Turabian PRAJAPATI MADHAVI, and J.S. DHOBI. "Clustering Method for Mixed Categorical and Numerical Data." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 2 number 3 ().
Vancouver PRAJAPATI MADHAVI, and J.S. DHOBI. Clustering Method for Mixed Categorical and Numerical Data. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2016 [Cited : ]; 2(3) : 3828-3836. Available from: https://ijariie.com/AdminUploadPdf/Clustering_Method_for_Mixed_Categorical_and_Numerical_Data_ijariie2501.pdf
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