Analysis & design of data farming algorithm for cardiac patient data

Shahnawaz, Mohd., Saxena, Kanak and Pandey, Hari Mohan (2018) Analysis & design of data farming algorithm for cardiac patient data. 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence). In: 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 11-12 Jan 2018, India. ISBN 9781538617199. [Conference or Workshop Item] (doi:10.1109/CONFLUENCE.2018.8442527)

[img]
Preview
PDF - Final accepted version (with author's formatting)
Download (984kB) | Preview

Abstract

Data farming is a process to grow data by applying various statistical, predictions, machine learning and data mining approach on the available data. As data collection cost is high so many times data mining projects use existing data collected for various other purposes, such as daily collected data to process and data required for monitoring & control. Sometimes, the dataset available might be large or wide data set and sufficient for extraction of knowledge but sometimes the data set might be narrow and insufficient to extract meaningful knowledge or the data may not even exist. Mining from wide datasets has received wide attention in the available literature. Many models and algorithms for data reduction & feature selection have been developed for wide datasets. Determining or extracting knowledge from a narrow data set (partial availability of data) or in the absence of an existing data set has not been sufficiently addressed in the literature. In this paper we propose an algorithm for data farming, which farm sufficient data from the available little seed data. Classification accuracy of J48 classification for farmed data is achieved better than classification results for the seed data, which proves that the proposed data farming algorithm is effective.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID: 24857
Notes on copyright: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Useful Links:
Depositing User: Dr Hari Mohan Pandey
Date Deposited: 30 Aug 2018 10:05
Last Modified: 09 Jun 2021 13:22
URI: https://eprints.mdx.ac.uk/id/eprint/24857

Actions (login required)

View Item View Item

Statistics

Downloads
Activity Overview
180Downloads
220Hits

Additional statistics are available via IRStats2.