Time Series Clustering- Introduction to Healthcare System
T. Rajesh1, K.V.G.Rao2

1Mr.T.Rajesh*, Asst Professor, GNITS, Shaikpet , Hyderabad, Telangana, India.
2Dr. K.V.G.Rao, Professor, GNITS, Shaikpet , Hyderabad, Telangana, India.

Manuscript received on October 18, 2019. | Revised Manuscript received on 24 October, 2019. | Manuscript published on November 10, 2019. | PP: 2958-2963 | Volume-9 Issue-1, November 2019. | Retrieval Number: A9115119119/2019©BEIESP | DOI: 10.35940/ijitee.A9115.119119
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract:  A Clustering technique is an appropriate solvable approach for classifying information while no existence of premature information pertaining to class labels, using promising techniques like cloud based computing and big data over latest years. Investigating awareness was gradually piled up with unsupervised methods such as clustering approaches to pull out useful information from the data set available. Time series based clustering data was used in most of the technical domains to extract information enriched patterns to power the data analysis which extracts useful essence from complicated as well as large data sets. It is mostly not possible for large datasets using classification approach whereas clustering approach will resolve the problem with aid of unsupervised techniques. In the proposed methodology, main spotlight on time series health care datasets, one of the kind of admired data in clustering approaches. This summary will expose 4 major components of Time series approaches.
Keywords: Clustering, Time-Series, Health Care Evaluation Measure, Representation.
Scope of the Article: Clustering