Life Expectancy and Mortality by Race Using Random Subspace Method
Yong Gyu Jung1, Dong Kyu Nam2, Hee Wan Kim3,
1Yong Gyu Jung, Department of Medical, Information Technology, Eulji University, Korea.
2Dong Kyu Nam, Chief Executive Officer, Project Jung, Co ltd., Korea.
3Hee Wan Kim, Division of Computer, Mechatronics, Shamyook University, Korea.
Manuscript received on 05 March 2019 | Revised Manuscript received on 12 March 2019 | Manuscript Published on 20 March 2019 | PP: 63-66 | Volume-8 Issue- 4S2 March 2019 | Retrieval Number: D1S0015028419/2019©BEIESP
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© 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: In recent years, massive data is pouring out in the information society. As collecting and processing of such vast amount of data is becoming an important issue, it is widely used with various fields of data mining techniques for extracting information based on data. In this paper, we analyze the causes of the difference between the expected life expectancy and the number of deaths by using the data of the expected life expectancy and the number of the deaths. To analyze the data effectively, we will use the REP-tree for a small and simple size problem using the Random subspace method, which is composed of random subspaces. The performance of the REP-tree algorithm was analyzed and evaluated for statistical data.
Keywords: Random Subspace, REP-tree, Racism, life Expectancy, Random Subspaces.
Scope of the Article: Information Retrieval