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Tagged with perceptron neural-networks
5 questions
10
votes
4
answers
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Can a perceptron with sigmoid activation function perform nonlinear classification?
Consider the perceptron as illustrated in the figure above.
I know:
If the activation function is linear, i.e. the first three cases, then
the perceptron is equivalent to a linear classifier.
...
- 243
22
votes
3
answers
16k
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From the Perceptron rule to Gradient Descent: How are Perceptrons with a sigmoid activation function different from Logistic Regression?
Essentially, my question is that in multilayer Perceptrons, perceptrons are used with a sigmoid activation function. So that in the update rule $\hat{y}$ is calculated as
$$\hat{y} = \frac{1}{1+\exp(...
user39663
2
votes
1
answer
220
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Would multilayer perceptrons be better than multiple regression?
I am using multiple regression to predict the future value of a time series from several other time series. Would doing this with multilayer perceptrons produce better results than multiple regression?...
- 459
1
vote
1
answer
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Bias input in neural network
Does bias input work like constant value in linear regression? and if bias input is not used then resulting boundary will always pass through origin?
Thanks in advance.
- 687
1
vote
1
answer
530
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Neural networks: how can convex optimization produce different weights each time?
I am training a multilayer perceptron with a logistic activation function by backpropagation. The weights are not unique - each time I redo the fit, I get a different set of weights. However the ...
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