A Variable Impacts Measurement in Random Forest for Mobile Cloud Computing
Joint Authors
Ihm, Sun-Young
Hur, Jae-Hee
Park, Young-Ho
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-09-07
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
Recently, the importance of mobile cloud computing has increased.
Mobile devices can collect personal data from various sensors within a shorter period of time and sensor-based data consists of valuable information from users.
Advanced computation power and data analysis technology based on cloud computing provide an opportunity to classify massive sensor data into given labels.
Random forest algorithm is known as black box model which is hardly able to interpret the hidden process inside.
In this paper, we propose a method that analyzes the variable impact in random forest algorithm to clarify which variable affects classification accuracy the most.
We apply Shapley Value with random forest to analyze the variable impact.
Under the assumption that every variable cooperates as players in the cooperative game situation, Shapley Value fairly distributes the payoff of variables.
Our proposed method calculates the relative contributions of the variables within its classification process.
In this paper, we analyze the influence of variables and list the priority of variables that affect classification accuracy result.
Our proposed method proves its suitability for data interpretation in black box model like a random forest so that the algorithm is applicable in mobile cloud computing environment.
American Psychological Association (APA)
Hur, Jae-Hee& Ihm, Sun-Young& Park, Young-Ho. 2017. A Variable Impacts Measurement in Random Forest for Mobile Cloud Computing. Wireless Communications and Mobile Computing،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1206102
Modern Language Association (MLA)
Hur, Jae-Hee…[et al.]. A Variable Impacts Measurement in Random Forest for Mobile Cloud Computing. Wireless Communications and Mobile Computing No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1206102
American Medical Association (AMA)
Hur, Jae-Hee& Ihm, Sun-Young& Park, Young-Ho. A Variable Impacts Measurement in Random Forest for Mobile Cloud Computing. Wireless Communications and Mobile Computing. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1206102
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1206102