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On the relationship between the support vector machine for classification and sparsified Fisher's linear discriminant
 Neural Processing Letters
, 1999
"... We show that the orientation and location of the separating hyperplane for 2class 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 ..."
Abstract

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We show that the orientation and location of the separating hyperplane for 2class 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.
2. Stationary Orbits in Old Quantum Mechanics 2.1 Quantized Planetary Atomic Model 2.2 Bohr’s Hypotheses and Quantized Circular Orbits 2.3 From Quantized Circles to Elliptical Orbits
, 2008
"... planetary model, FrankHertz experiment, Infinite square well potential, ..."