Statistical Pattern Recognition, Second Edition

By A. Webb. 2002

589 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/04a6bce6b3e58b0b15321b282f8796b912bdacfe

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

Citations in the corpus

A survey on face detection in the wild: Past, present and future (2015, methodology): “In [123] a cascade learning algorithm based on forward feature selection [124] was proposed.”
Visualization and interactive feature selection for unsupervised data (2000, methodology): “Y x xxxxxx xxxxxx xx xxx x xxxxx xxx xx xx xxx xx xx xx x xxx x xxx xx x x xx xxxx xxxx xxx xxx xxxx x xx xxxxx x x x xxxxxxxx x x xx x xxxx x Figure2:LDAhoosesthey-axis,whereaspeA hoosesthex-axis.”
A Novel Template Reduction Approach for the K -Nearest Neighbor Method (2009, background): “Its simplicity and effectiveness has led to it being widely used in a large number of classification problems, including handwritten digits, satellite image scenes and medical diagnosis [1] [2] [3] [4] [5].”
Structure-Preserving Color Normalization and Sparse Stain Separation for Histological Images (2016, methodology): “For example, the authors proposed to use a piece-wise linear decomposition instead of a linear one in case of a poor stain-cluster separation but they have not provided a quantitative threshold for fisher criteria [22] to determine ‘poor’ clusters.”
Classifying depression patients and normal subjects using machine learning techniques (2011, background): “LDA finds linear combination of features to classify two or more classes [20].”
Feature Selection for Unsupervised Learning (2004, methodology): “, the criterion value monotonically increases as features are added assuming identical clustering assignments (Fukunaga, 1990; Narendra and Fukunaga, 1977).”