Fill in the blanks with the correct selection from the drop down menu. that is used in most neural network models today. The neuron contains a number of that represent data that defines the problem to be learned; 2. w, which is a set of + that that determines an overall The sigmoid neuron is the main parts: 1. x, which is a set of + that represent how important a piece of data is to the neuron; 3. g, which is a(n) determines an overall value of all the data associated with the neuron; 4. f, which is a(n) output value of the neuron; 5. a(n) which automatically finds the "optimal" values for w.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Fill in the blanks with the correct selection from the drop down menu with questions about networks
Fill in the blanks with the correct selection from the drop down menu.
that is used in most neural network models today. The neuron contains a number of
that represent data that defines the problem to be learned; 2. w, which is a set of
+ that
that determines an overall
The sigmoid neuron is the
main parts: 1. x, which is a set of
+ that represent how important a piece of data is to the neuron; 3. g, which is a(n)
determines an overall value of all the data associated with the neuron; 4. f, which is a(n)
output value of the neuron; 5. a(n)
which automatically finds the "optimal" values for w.
Transcribed Image Text:Fill in the blanks with the correct selection from the drop down menu. that is used in most neural network models today. The neuron contains a number of that represent data that defines the problem to be learned; 2. w, which is a set of + that that determines an overall The sigmoid neuron is the main parts: 1. x, which is a set of + that represent how important a piece of data is to the neuron; 3. g, which is a(n) determines an overall value of all the data associated with the neuron; 4. f, which is a(n) output value of the neuron; 5. a(n) which automatically finds the "optimal" values for w.
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