Feature selection and classification problem in bioinformatics.

• Other Authors: Lau, Siu Him.
• Format: Others
• Language: English; Chinese
• Published: 2010
• Subjects: Bioinformatics; Diabetes > Genetic aspects; Computational Biology; Medical Informatics; Diabetes Mellitus > genetics
• Online Access: http://library.cuhk.edu.hk/record=b5894280; http://repository.lib.cuhk.edu.hk/en/item/cuhk-327001

Lau, Siu Him. === "November 2009." === Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. === Includes bibliographical references (leaves 46). === Abstracts in English and Chinese. === Chapter 1 --- Introduction --- p.7 === Chapter 2 --- Support Vector Machine --- p.9 === Chapter 2.1 --- Two-Class Support Vector Machine --- p.9 === Chapter 2.2 --- Kernel Tricks --- p.12 === Chapter 2.3 --- Weighted Support Vector Machine --- p.14 === Chapter 2.4 --- Parameter Selection in Support Vector Machine --- p.16 === Chapter 3 --- Feature Selection Methods --- p.17 === Chapter 3.1 --- Principle Component Analysis --- p.17 === Chapter 3.1.1 --- Maximizing Variance --- p.17 === Chapter 3.1.2 --- Relation with Singular Value Decomposition --- p.19 === Chapter 3.1.3 --- Feature Selection by Singular Value Decomposition --- p.20 === Chapter 3.1.4 --- Disadvantage of Unsupervised Learning --- p.21 === Chapter 3.2 --- Linear Discriminant Analysis --- p.21 === Chapter 3.2.1 --- Between-class Distance and Within-class Variance --- p.22 === Chapter 3.2.2 --- Generalized Eigenvalue Problem --- p.24 === Chapter 3.2.3 --- Feature Selection by Linear Discriminant Analysis --- p.25 === Chapter 4 --- Application on a Real Problem --- p.27 === Chapter 4.1 --- Problem and Goals --- p.27 === Chapter 4.2 --- Diabetes Data Set --- p.27 === Chapter 4.3 --- Data Processing --- p.28 === Chapter 4.3.1 --- Pre-processing for Categorical Data --- p.28 === Chapter 4.3.2 --- Handling Uneven Data Set --- p.31 === Chapter 5 --- Results on Simulated and Real Data --- p.33 === Chapter 5.1 --- Evaluation --- p.33 === Chapter 5.1.1 --- Training and Testing --- p.33 === Chapter 5.1.2 --- Evaluation Method --- p.34 === Chapter 5.2 --- Classification Procedure --- p.35 === Chapter 5.3 --- Performance on Simulated Data --- p.36 === Chapter 5.4 --- Results on a Real Data Set --- p.39 === Chapter 5.4.1 --- Features Selection --- p.39 === Chapter 5.4.2 --- Performance on the Real Data Set --- p.41 === Chapter 5.4.3 --- Analysis on Risk Factors --- p.42 === Chapter 6 --- Conclusion --- p.44 === Bibliography --- p.46