Learning Machines: Foundations of Trainable Pattern-classifying SystemsMcGraw-Hill, 1965 - 137 sivua |
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Tulokset 1 - 3 kokonaismäärästä 9
Sivu 77
... perceptrons . During this period Widrow was pursuing engineering applications of trainable TLUs which he called ... Perceptron : A Perceiving and Recognizing Automaton , Project PARA , Cornell Aeronautical Laboratory Report 85-460-1 ...
... perceptrons . During this period Widrow was pursuing engineering applications of trainable TLUs which he called ... Perceptron : A Perceiving and Recognizing Automaton , Project PARA , Cornell Aeronautical Laboratory Report 85-460-1 ...
Sivu 78
... Perceptrons and the Theory of Brain Mechanisms , " Spartan Books , Washington , D.C. , 1961 . 7 Block , H .: The Perceptron : A Model for Brain Functioning , I. , Reviews of Modern Physics , vol . 34 , pp . 123-135 , January , 1962 ...
... Perceptrons and the Theory of Brain Mechanisms , " Spartan Books , Washington , D.C. , 1961 . 7 Block , H .: The Perceptron : A Model for Brain Functioning , I. , Reviews of Modern Physics , vol . 34 , pp . 123-135 , January , 1962 ...
Sivu 93
... Perceptron Theory , Cornell Aeronautical Laboratory Report VG - 1196 - G - 7 , Buffalo , New York , June , 1960 . 3 Block , H. D .: The Perceptron : A Model for Brain Functioning , I , Reviews of Modern Physics , vol . 34 , pp . 123–135 ...
... Perceptron Theory , Cornell Aeronautical Laboratory Report VG - 1196 - G - 7 , Buffalo , New York , June , 1960 . 3 Block , H. D .: The Perceptron : A Model for Brain Functioning , I , Reviews of Modern Physics , vol . 34 , pp . 123–135 ...
Sisältö
TRAINABLE PATTERN CLASSIFIERS | 1 |
PARAMETRIC TRAINING METHODS | 43 |
SOME NONPARAMETRIC TRAINING METHODS | 65 |
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adjusted apply assume bank belonging to category called changes Chapter cluster committee components consider consists contains correction corresponding decision surfaces define denote density depends derivation described Development discriminant functions discussed distance distribution element equal error-correction estimates example exists expression FIGURE fixed given implemented important initial layered machine linear dichotomies linear discriminant functions linear machine linearly separable measurements negative networks normal Note optimum origin parameters partition pattern classifier pattern hyperplane pattern space pattern vector piecewise linear plane points positive presented probability problem proof properties proved PWL machine quadric reduced regions respect response rule sample mean selection separable shown side space Stanford step subsidiary discriminant Suppose theorem theory threshold training methods training procedure training sequence training subsets transformation values weight vectors zero
Viitteet tähän teokseen
A Probabilistic Theory of Pattern Recognition Luc Devroye,László Györfi,Gabor Lugosi Rajoitettu esikatselu - 1997 |