Learning Machines: Foundations of Trainable Pattern-classifying SystemsMcGraw-Hill, 1965 - 137 pagina's |
Inhoudsopgave
TRAINABLE PATTERN CLASSIFIERS | 1 |
PARAMETRIC TRAINING METHODS | 43 |
SOME NONPARAMETRIC TRAINING METHODS | 65 |
Copyright | |
3 andere gedeelten niet getoond
Overige edities - Alles bekijken
Learning Machines: Foundations of Trainable Pattern-classifying Systems Nils J. Nilsson Fragmentweergave - 1965 |
Learning Machines: Foundations of Trainable Pattern-classifying Systems Nils J. Nilsson Fragmentweergave - 1965 |
Learning Machines: Foundations of Trainable Pattern-classifying Systems Nils J. Nilsson Fragmentweergave - 1965 |
Veelvoorkomende woorden en zinsdelen
adjusted apply assume bank called cells changes Chapter classifier cluster column committee machine components consider consists contains correction corresponding covariance decision surfaces define denote density depends described discriminant functions discussed distance distributions elements equal error-correction estimates example exist expression FIGURE fixed given implemented initial layered machine linear machine linearly separable lines majority matrix mean measurements modes negative networks nonparametric normal Note optimum origin parameters partition pattern hyperplane pattern space pattern vector pattern-classifying piecewise linear plane points positive presented probability problem properties PWL machine quadric regions respect response rule selection separable sequence side solution space Stanford step subsidiary discriminant Suppose theorem theory threshold training methods training patterns training procedure training sequence training subsets transformation values weight vectors X1 and X2 Y₁ zero
Verwijzingen naar dit boek
A Probabilistic Theory of Pattern Recognition Luc Devroye,László Györfi,Gabor Lugosi Gedeeltelijke weergave - 1997 |