Difference between revisions of "TDSM 11.11"

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in neural network if we define a network with n inputs ,no hidden layer and one output, the result will be the weighted sum of the inputs in the output and this is the same as logistic regression.
 
in neural network if we define a network with n inputs ,no hidden layer and one output, the result will be the weighted sum of the inputs in the output and this is the same as logistic regression.
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[[File:neural_networks.jpg|200px|thumb|left|Neural Networks]]

Latest revision as of 07:55, 13 December 2017

If we have n dimensions, with features [math] x_1,x_2,...,x_n[/math] the logistic regression is a function of x as follow:

[math]f(x)=w_1x_1+...+w_nx_n[/math]

in neural network if we define a network with n inputs ,no hidden layer and one output, the result will be the weighted sum of the inputs in the output and this is the same as logistic regression.


Edit :

Neural Networks