@inproceedings{2ddcc5844b7b499cb0668366fed4a6ff,
title = "Effective cancer classification based on gene expression data using multidimensional mutual information and ELM",
abstract = "In the field of microarray data research, it is quite challenging to make classification due to small sample size and the high dimension of data. Moreover, the feature selection is crucial. In this paper, we propose multidimensional mutual information (MMI) feature selection method to select the most informative features for classification. After feature selection using the proposed MMI, Extreme Learning Machine (ELM) is used as an efficient classifier. So as to evaluate the performance of the proposed methodology, a typical dataset called Leukemia is selected to carry out a case study. Simulation results demonstrate the effectiveness of the proposed method.",
keywords = "Gene expression data, classification, extreme machine learning, feature selection, information gain",
author = "Zhu, \{Qun Xiong\} and Yuan Fan and He, \{Yan Lin\} and Yuan Xu",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018 ; Conference date: 25-05-2018 Through 27-05-2018",
year = "2018",
month = oct,
day = "30",
doi = "10.1109/DDCLS.2018.8515927",
language = "English",
series = "Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "954--958",
booktitle = "Proceedings of 2018 IEEE 7th Data Driven Control and Learning Systems Conference, DDCLS 2018",
address = "United States",
}
