Learning Machines: Foundations of Trainable Pattern-classifying Systems

Etukansi
McGraw-Hill, 1965 - 137 sivua
0 Arvostelut
Arvosteluja ei vahvisteta, mutta Google tarkistaa ne valheellisen sisällön varalta ja poistaa tällaisen sisällön

Kirjan sisältä

 

Tulokset 1 - 3 kokonaismäärästä 37

Sivu 28
equal to zero only for X = 0 ( ) 0 When these conditions are met , both the matrix A and the quadratic form are called positive definite . If A has one or more of its eigenvalues equal to zero and all the others positive , then the ...
Sivu 67
locus of all weight points for which W.Y = 0 ( 4.2 ) The hyperplane in weight space defined by Eq . ( 4-2 ) for a given pattern vector is called the pattern hyperplane . This hyperplane separates the space of weight points into two ...
Sivu 69
That is , W ' WcY = ( 4 · 4 ) where c is a positive number called the correction increment . It controls the extent of the adjustment . For sufficiently large c , the weight point will cross the pattern hyperplane , and Y. W ' will be ...

Missä on loput tästä teoksesta?

Mitä ihmiset sanovat - Kirjoita arvostelu

Yhtään arvostelua ei löytynyt.

Sisältö

TRAINABLE PATTERN CLASSIFIERS
1
PARAMETRIC TRAINING METHODS
43
SOME NONPARAMETRIC TRAINING METHODS
65
Tekijänoikeudet

3 muita osia ei näytetty

Muita painoksia - Näytä kaikki

Learning Machines: Foundations of Trainable Pattern-classifying Systems
Nils J. Nilsson
Otenäkymä - 1965
Learning Machines: Foundations of Trainable Pattern-classifying Systems
Nils J. Nilsson
Otenäkymä - 1965
Learning Machines: Foundations of Trainable Pattern-classifying Systems
Nils J. Nilsson
Otenäkymä - 1965
Näytä kaikki »

Yleiset termit ja lausekkeet

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 step subsidiary discriminant Suppose terns theorem theory threshold training methods training patterns training procedure training sequence training subsets transformation values weight vectors X1 and X2 Y₁ zero

Viitteet tähän teokseen

Tietoja kirjailijasta (1965)

Nils John Nilsson was born in Saginaw, Michigan on February 6, 1933. He received a bachelor's degree and a Ph.D. in electrical engineering from Stanford University. He joined the Air Force and served three years at the Rome Air Development Center before joining the Stanford Research Institute in 1961. He helped develop the first general-purpose robot and was a co-inventor of algorithms that made it possible for the machine to move about efficiently and perform simple tasks. He later worked on the "Computer-based Consultant," which focused on natural language understanding. He wrote several books including Learning Machines: Foundations of Trainable Pattern-Classifying Systems and The Quest for Artificial Intelligence: A History of Ideas and Achievements. He died on April 21, 2019 at the age of 86.

Kirjaluettelon tiedot

QR code for Learning Machines
OtsikkoLearning Machines: Foundations of Trainable Pattern-classifying Systems
McGraw-Hill series in systems science
KirjoittajaNils J. Nilsson
Painoskuvitettu
KustantajaMcGraw-Hill, 1965
Alkuperäisteoksen sijaintiWisconsinin yliopisto - Madison
Digitoitu16. huhtikuu 2008
ISBN0070465703, 9780070465701
Pituus137 sivua
  
Vie sitaattiBiBTeX EndNote RefMan