Learning Machines: Foundations of Trainable Pattern-classifying Systems

Etukansi
McGraw-Hill, 1965 - 137 sivua
0 Arvostelut

Kirjan sisältä

 

Tulokset 1 - 3 kokonaismäärästä 17

Sivu 69
In the error - correction training procedures , the training patterns are presented to the trainable TLU one at a time for trial . The trial consists of comparing the actual response of the TLU with the desired response dictated by the ...
Sivu 75
A generalized error - correction procedure can be used to train the general linear machine and thus find ( solution ) weight vectors when they exist . In this procedure , each pattern in y is presented one at a time in any sequence .
Sivu 123
The following training method is presented because it illustrates several that have been proposed for mode seeking . No rigorous theoretical treatment has been advanced to support it , and only limited empirical evidence has been ...

Missä on loput tästä teoksesta?

Mitä ihmiset sanovat - Kirjoita arvostelu

Yhtään arvostelua ei löytynyt.

Sisältö

SOME NONPARAMETRIC TRAINING METHODS
65
6
95
7
115
Tekijänoikeudet

2 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 belonging to category called changes Chapter cluster committee components consider consists contains correction corresponding covariance 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 illustrated implemented important initial layered machine linear dichotomies linear machine linearly separable matrix measurements negative networks normal Note optimum origin parameters partition pattern classifier pattern hyperplane pattern space pattern vector patterns belonging 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 Suppose theorem theory threshold training methods training procedure training sequence training subsets transformation values weight vectors 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
ISBN0070465703, 9780070465701
Pituus137 sivua
  
Vie sitaattiBiBTeX EndNote RefMan