A Comparative Study in Predictive Analytic Frameworks in Big Data
- Title
- A Comparative Study in Predictive Analytic Frameworks in Big Data
- Creator
- Sudharson D.; Vignesh K.; Suganthi B.; Arunkkumar B.; Vijay S.; Logita S.
- Description
- Every information processing sector uses predictive analytic framework in terms of distributed datasets through a variety of applications. These analytic frameworks are effectively used for various analyses of data, parameter, and attributes. Leveraging data to make insightful decisions for maximizing the effectiveness requires the determination of the best predictive framework for any organization. Even a retail unit which wants to scale up its production rely on multiple parameters. These parameters must be analyzed for effective quality control in any domain. Since there are diversities in every domain the data will be in varied form, and these are accumulated as Big Data. These analyses are done using machine learning frameworks. The strategy involved would differ from one domain to another such as in the health care sector the framework might predict the magnitude of patients admitted to the urgent care facility over the upcoming days whereas in the production industry the framework would align quality control measures. This article analyses a few domains and their deployed machine learning impacts in a strategic way. 2023 American Institute of Physics Inc.. All rights reserved.
- Source
- AIP Conference Proceedings, Vol-2914, No. 1
- Date
- 2023-01-01
- Publisher
- American Institute of Physics Inc.
- Coverage
- Sudharson D., Kumaraguru College of Technology, Coimbatore, India; Vignesh K., Christ Deemed to be University, Bangalore, India; Suganthi B., RVS College of Engineering and Technology, Coimbatore, India; Arunkkumar B., Sri Krishna College of Engineering and Technology, Coimbatore, India; Vijay S., Kumaraguru College of Technology, Coimbatore, India; Logita S., Kumaraguru College of Technology, Coimbatore, India
- Rights
- Restricted Access
- Relation
- ISSN: 0094243X; ISBN: 978-073544770-7
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Sudharson D.; Vignesh K.; Suganthi B.; Arunkkumar B.; Vijay S.; Logita S., “A Comparative Study in Predictive Analytic Frameworks in Big Data,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19556.