Questions tagged [perceptron]
An early example of neural network without any hidden layers and with a single (possibly nonlinear) output unit.
6
questions
33
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6answers
30k views
What's the difference between logistic regression and perceptron?
I'm going through Andrew Ng's lecture notes on Machine Learning.
The notes introduce us to logistic regression and then to perceptron. While describing Perceptron, the notes say that we just change ...
21
votes
3answers
14k views
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(...
8
votes
4answers
10k views
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.
...
1
vote
1answer
145 views
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?...
1
vote
2answers
3k views
Perceptron overfitting?
I'm trying to judge the performance of my perceptron linear discriminant. In one instance I'm training on a sample size of 150 and on another I'm training on a sample size of 1500. I test both of ...
0
votes
1answer
556 views
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.
