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@article{ART002419226},
author={Jeong， Yu-jeong and Choi Gwang Mi},
title={A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2018},
volume={23},
number={12},
pages={43-48},
doi={10.9708/jksci.2018.23.12.043}

TY - JOUR
AU - Jeong， Yu-jeong
AU - Choi Gwang Mi
TI - A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis
JO - Journal of The Korea Society of Computer and Information
PY - 2018
VL - 23
IS - 12
PB - The Korean Society Of Computer And Information
SP - 43
EP - 48
SN - 1598-849X
AB - In this paper, more efficient classification result could be obtained by applying the combination of the Hidden Markov Model and SVM Model to HMSV algorithm gene expression data which simulated the stochastic flow of gene data and clustering it. In this paper, we verified the HMSV algorithm that combines independently learned algorithms. To prove that this paper is superior to other papers, we tested the sensitivity and specificity of the most commonly used classification criteria. As a result, the K-means is 71% and the SOM is 68%. The proposed HMSV algorithm is 85%. These results are stable and high. It can be seen that this is better classified than using a general classification algorithm. The algorithm proposed in this paper is a stochastic modeling of the generation process of the characteristics included in the signal, and a good recognition rate can be obtained with a small amount of calculation, so it will be useful to study the relationship with diseases by showing fast and effective performance improvement with an algorithm that clusters nodes by simulating the stochastic flow of Gene Data through data mining of BigData.
KW - BigData;Data Mining Gene Data;Classification System
DO - 10.9708/jksci.2018.23.12.043
ER -

Jeong， Yu-jeong and Choi Gwang Mi. (2018). A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis. Journal of The Korea Society of Computer and Information, 23(12), 43-48.

Jeong， Yu-jeong and Choi Gwang Mi. 2018, "A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis", Journal of The Korea Society of Computer and Information, vol.23, no.12 pp.43-48. Available from: doi:10.9708/jksci.2018.23.12.043

Jeong， Yu-jeong, Choi Gwang Mi "A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis" Journal of The Korea Society of Computer and Information 23.12 pp.43-48 (2018) : 43.

Jeong， Yu-jeong, Choi Gwang Mi. A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis. 2018; 23(12), 43-48. Available from: doi:10.9708/jksci.2018.23.12.043

Jeong， Yu-jeong and Choi Gwang Mi. "A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis" Journal of The Korea Society of Computer and Information 23, no.12 (2018) : 43-48.doi: 10.9708/jksci.2018.23.12.043

Jeong， Yu-jeong; Choi Gwang Mi. A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis. Journal of The Korea Society of Computer and Information, 23(12), 43-48. doi: 10.9708/jksci.2018.23.12.043

Jeong， Yu-jeong; Choi Gwang Mi. A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis. Journal of The Korea Society of Computer and Information. 2018; 23(12) 43-48. doi: 10.9708/jksci.2018.23.12.043

Jeong， Yu-jeong, Choi Gwang Mi. A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis. 2018; 23(12), 43-48. Available from: doi:10.9708/jksci.2018.23.12.043

Jeong， Yu-jeong and Choi Gwang Mi. "A Implementation of Optimal Multiple Classification System using Data Mining for Genome Analysis" Journal of The Korea Society of Computer and Information 23, no.12 (2018) : 43-48.doi: 10.9708/jksci.2018.23.12.043