Difference between revisions of "TDSM 11.11"
From The Data Science Design Manual Wikia
(Created page with "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 netw...") |
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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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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.
