Modern Multivariate Statistical Techniques Regression, Classification, and Manifold Learning /

Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics. These exciti...

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Bibliographic Details
Main Author: Izenman, Alan J. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2008.
Series:Springer Texts in Statistics,
Subjects:
Online Access:Full Text via HEAL-Link
Table of Contents:
  • and Preview
  • Data and Databases
  • Random Vectors and Matrices
  • Nonparametric Density Estimation
  • Model Assessment and Selection in Multiple Regression
  • Multivariate Regression
  • Linear Dimensionality Reduction
  • Linear Discriminant Analysis
  • Recursive Partitioning and Tree-Based Methods
  • Artificial Neural Networks
  • Support Vector Machines
  • Cluster Analysis
  • Multidimensional Scaling and Distance Geometry
  • Committee Machines
  • Latent Variable Models for Blind Source Separation
  • Nonlinear Dimensionality Reduction and Manifold Learning
  • Correspondence Analysis.