Chrysanthemum Abnormal Petal Type Classification using Random Forest and Over-sampling

Peisen Yuan; Shougang Ren; Huanliang Xu; Jin Chen

doi:10.1109/BIBM.2018.8621234

Chrysanthemum Abnormal Petal Type Classification using Random Forest and Over-sampling

Peisen Yuan
, Shougang Ren
, Huanliang Xu
, Jin Chen

Internal Medicine

Producción científica: Conference contribution › revisión exhaustiva

5 Citas (Scopus)

Resumen

Phenotype-based chrysanthemum petal classification, integrated with genomic sequencing, is critical for studying chrysanthemum phenotypic taxonomy. In this article, a new pipeline has been established towards automatic classification of chrysanthemum flower petal types. First, a set of phenotypic data of chrysanthemum flowers was collected. Second, we adopted random forest to classify the chrysanthemum flower petal types, and adopted over-sampling techniques to address the imbalanced label problem. Third, we systematically evaluated feature combinations regarding their influences to the classification results. Experimental results show that our method can successfully classify chrysanthemum flower petal types on an imbalanced chrysanthemum data.

Idioma original	English
Título de la publicación alojada	Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Editores	Harald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang
Páginas	275-278
Número de páginas	4
ISBN (versión digital)	9781538654880
DOI	https://doi.org/10.1109/BIBM.2018.8621234
Estado	Published - ene 21 2019
Evento	2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 - Madrid, Spain Duración: dic 3 2018 → dic 6 2018

Serie de la publicación

Nombre	Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

Conference

Conference	2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
País/Territorio	Spain
Ciudad	Madrid
Período	12/3/18 → 12/6/18

Nota bibliográfica

Publisher Copyright:
© 2018 IEEE.

Financiación

This work is supported by NSFC grants (No.61502236), the Fundamental Research Funds for the Central Universities(No.KYZ201752), and National Science Foundation ABI program (No.1458556).

Financiadores	Número del financiador
National Science Foundation (NSF)	1458556
National Natural Science Foundation of China (NSFC)	61502236
Fundamental Research Funds for the Central Universities	No.KYZ201752

ASJC Scopus subject areas

Biomedical Engineering
Health Informatics

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10.1109/BIBM.2018.8621234

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Yuan, P., Ren, S., Xu, H., & Chen, J. (2019). Chrysanthemum Abnormal Petal Type Classification using Random Forest and Over-sampling. En H. Schmidt, D. Griol, H. Wang, J. Baumbach, H. Zheng, Z. Callejas, X. Hu, J. Dickerson, & L. Zhang (Eds.), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 (pp. 275-278). Artículo 8621234 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). https://doi.org/10.1109/BIBM.2018.8621234

Yuan, Peisen ; Ren, Shougang ; Xu, Huanliang et al. / Chrysanthemum Abnormal Petal Type Classification using Random Forest and Over-sampling. Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. editor / Harald Schmidt ; David Griol ; Haiying Wang ; Jan Baumbach ; Huiru Zheng ; Zoraida Callejas ; Xiaohua Hu ; Julie Dickerson ; Le Zhang. 2019. pp. 275-278 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

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title = "Chrysanthemum Abnormal Petal Type Classification using Random Forest and Over-sampling",

abstract = "Phenotype-based chrysanthemum petal classification, integrated with genomic sequencing, is critical for studying chrysanthemum phenotypic taxonomy. In this article, a new pipeline has been established towards automatic classification of chrysanthemum flower petal types. First, a set of phenotypic data of chrysanthemum flowers was collected. Second, we adopted random forest to classify the chrysanthemum flower petal types, and adopted over-sampling techniques to address the imbalanced label problem. Third, we systematically evaluated feature combinations regarding their influences to the classification results. Experimental results show that our method can successfully classify chrysanthemum flower petal types on an imbalanced chrysanthemum data.",

keywords = "Chrysanthemum, imbalanced data, oversampling, phenotypic classification, random forest",

author = "Peisen Yuan and Shougang Ren and Huanliang Xu and Jin Chen",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 ; Conference date: 03-12-2018 Through 06-12-2018",

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Yuan, P, Ren, S, Xu, H & Chen, J 2019, Chrysanthemum Abnormal Petal Type Classification using Random Forest and Over-sampling. En H Schmidt, D Griol, H Wang, J Baumbach, H Zheng, Z Callejas, X Hu, J Dickerson & L Zhang (eds.), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018., 8621234, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, pp. 275-278, 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, Madrid, Spain, 12/3/18. https://doi.org/10.1109/BIBM.2018.8621234

Chrysanthemum Abnormal Petal Type Classification using Random Forest and Over-sampling. / Yuan, Peisen; Ren, Shougang; Xu, Huanliang et al.
Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. ed. / Harald Schmidt; David Griol; Haiying Wang; Jan Baumbach; Huiru Zheng; Zoraida Callejas; Xiaohua Hu; Julie Dickerson; Le Zhang. 2019. p. 275-278 8621234 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

Producción científica: Conference contribution › revisión exhaustiva

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AU - Yuan, Peisen

AU - Ren, Shougang

AU - Xu, Huanliang

AU - Chen, Jin

PY - 2019/1/21

Y1 - 2019/1/21

N2 - Phenotype-based chrysanthemum petal classification, integrated with genomic sequencing, is critical for studying chrysanthemum phenotypic taxonomy. In this article, a new pipeline has been established towards automatic classification of chrysanthemum flower petal types. First, a set of phenotypic data of chrysanthemum flowers was collected. Second, we adopted random forest to classify the chrysanthemum flower petal types, and adopted over-sampling techniques to address the imbalanced label problem. Third, we systematically evaluated feature combinations regarding their influences to the classification results. Experimental results show that our method can successfully classify chrysanthemum flower petal types on an imbalanced chrysanthemum data.

AB - Phenotype-based chrysanthemum petal classification, integrated with genomic sequencing, is critical for studying chrysanthemum phenotypic taxonomy. In this article, a new pipeline has been established towards automatic classification of chrysanthemum flower petal types. First, a set of phenotypic data of chrysanthemum flowers was collected. Second, we adopted random forest to classify the chrysanthemum flower petal types, and adopted over-sampling techniques to address the imbalanced label problem. Third, we systematically evaluated feature combinations regarding their influences to the classification results. Experimental results show that our method can successfully classify chrysanthemum flower petal types on an imbalanced chrysanthemum data.

KW - Chrysanthemum

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KW - oversampling

KW - phenotypic classification

KW - random forest

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ER -

Yuan P, Ren S, Xu H, Chen J. Chrysanthemum Abnormal Petal Type Classification using Random Forest and Over-sampling. En Schmidt H, Griol D, Wang H, Baumbach J, Zheng H, Callejas Z, Hu X, Dickerson J, Zhang L, editores, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. 2019. p. 275-278. 8621234. (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). doi: 10.1109/BIBM.2018.8621234

Chrysanthemum Abnormal Petal Type Classification using Random Forest and Over-sampling

Resumen

Serie de la publicación

Conference

Nota bibliográfica

Financiación

ASJC Scopus subject areas

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