
Time Series Clustering- Introduction to Healthcare System
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a9115.119119
Subject(s) - cluster analysis , computer science , data mining , class (philosophy) , big data , series (stratigraphy) , set (abstract data type) , data set , conceptual clustering , consensus clustering , clustering high dimensional data , machine learning , artificial intelligence , correlation clustering , cure data clustering algorithm , paleontology , biology , programming language
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.