On the relationship between the support vector machine for classification and sparsified Fisher's linear discriminant

On the relationship between the support vector machine for classification and sparsified Fisher's linear discriminant (1999)

by A. Amnon Shashua

Venue:	Neural Processing Letters
Citations:	10 - 0 self

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Datum	Value	Source
TITLE	On the relationship between the support vector machine for classification and sparsified Fisher's linear discriminant	user correction
AUTHOR NAME	A. Amnon Shashua	user correction
AUTHOR AFFIL	Institute of Computer Science; Hebrew University of Jerusalem	user correction
AUTHOR ADDR	91904 Jerusalem, Israel	user correction
ABSTRACT	We show that the orientation and location of the separating hyperplane for 2-class supervised pattern classification obtained by the Support Vector Machine (SVM) proposed by Vapnik and his colleagues, is equivalent to the solution obtained by Fisher's Linear Discriminant on the set of Support Vectors. In other words, SVM can be seen as a way to "sparsify" Fisher's Linear Discriminant in order to obtain the most generalizing classification from the training set.	user correction
YEAR	1999	INFERENCE
VENUE	Neural Processing Letters	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	129--139	INFERENCE
VOLUME	9	INFERENCE
CITATIONS	14 found	ParsCit 1.0