PANTSA Influence in grouping Mixed and Incomplete Data
Yusbel Chávez-Castilla

Yusbel Chávez-Castilla, Computer Science Department, University of Ciego de Ávila, Cuba.

Manuscript received on November 13, 2019. | Revised Manuscript received on 25 November, 2019. | Manuscript published on December 10, 2019. | PP: 579-583 | Volume-9 Issue-2, December 2019. | Retrieval Number: B6534129219/2019©BEIESP | DOI: 10.35940/ijitee.B6534.129219
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Abstract: Obtaining high quality groups and processing mixed and incomplete data (DMI) are still problems in the data clustering. Recently a method was proposed that improves the results obtained by clustering algorithms, the PAntSA; but this was only designed and tested for numerical data. For this reason, this paper analyzes the influence of applying the PAntSA in the performance of DMI restricted clustering algorithms. For this, the results of different algorithms are compared before and after applying the PAntSA. The comparisons made provide experimental evidence that the PAntSA algorithm improves the quality of the groups obtained by traditional DMI clustering methods. 
Keywords:  About Four Key Words or Phrases in Alphabetical order, Separated by Commas.
Scope of the Article: Data Analytics