Paper Title:
PCA for Leukemia Classification
  Abstract

The real cause of leukemia has not been found, and traditional method to recognize the malignant cells has some limitations, and that is very time-consuming. Because microarray gene expression data is few samples, high-dimensional and nonlinear, it brings us “dimensionality disaster”, so data dimensionality reduction becomes a problem we pay attention, and SVM (Support Vector Machine) overcomes the “dimensionality disaster” to a certain extent by means of optimization method, for the decision function of SVM is only decided by part of the support vectors. This paper combines SVM with Laplacian Eigenmaps and PCA (Principal Component Analysis) respectively for Leukemia data classification, compare the results, PCA gets better result.

  Info
Periodical
Edited by
Long Chen, Yongkang Zhang, Aixing Feng, Zhenying Xu, Boquan Li and Han Shen
Pages
744-747
DOI
10.4028/www.scientific.net/AMM.43.744
Citation
J. Li, G. R. Weng, "PCA for Leukemia Classification", Applied Mechanics and Materials, Vol. 43, pp. 744-747, 2011
Online since
December 2010
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Yan Gao
Abstract:For poor accuracy of detection of the urban traffic network classification, the Support Vector Machine (SVM)is applied to classification of...
489
Authors: Wen Jie Wu, Da Gui Huang, Zheng Dong
Abstract:This paper describes a support vector machine(SVM) approach to improve the test validity and accuracy for Aero-engine fault diagnosis. A new...
811
Authors: Quan Sheng Jiang, Su Ping Li
Chapter 10: Environmentally Sustainable Manufacturing Processes and Systems
Abstract:Manifold learning algorithms are nonlinear dimensionality reduction algorithms rising in recent years. Laplacian Eigenmaps is a typical...
2679
Authors: Bai Lin Liu, Li Xing Gao
Chapter 6: Measurement Techniques, Technologies and Equipment
Abstract:To solve the problem that large training samples and slow speed in diagnosing based on support vector classifier, a hybrid classification...
887
Authors: Ru Zhang
Chapter 6: Data Acquisition and Data Processing, Computational Techniques
Abstract:With the ceramics market's developing, the use of image processing and intelligent algorithm is applied to the ancient ceramics recognition...
1201