Abstract
Feature gene selection of tumor classification is an important means to find the expression of tumor-specific genes. To study the tumor gene expression pattern, k-means clustering analysis method is considered. It is used for selecting the best genetic center, extracting scalar features and determining the corresponding gene label. The experimental results show that the correct rate of the classification results by this method is 87 %.
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Cong, L., Ruan, W. (2013). K-Mean Clustering Analysis and Its Applications to Classification of Tumor Gene. In: Du, W. (eds) Informatics and Management Science III. Lecture Notes in Electrical Engineering, vol 206. Springer, London. https://doi.org/10.1007/978-1-4471-4790-9_91
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DOI: https://doi.org/10.1007/978-1-4471-4790-9_91
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Publisher Name: Springer, London
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Online ISBN: 978-1-4471-4790-9
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