Questions tagged [perceptron]
For questions about the perceptron learning algorithm in Machine Learning.
2
votes
1answer
32 views
Can a neuron have both a bias and a threshold?
I have not seen a neuron that uses both a bias and a threshold. Why is this?
1
vote
0answers
37 views
How do two perceptrons produce different linear decision boundaries when learning?
I've learned that you can use two perceptrons to ultimately create a classifier for non-linearly separable data. I'm trying to understand how / if these two perceptrons converge to two different ...
1
vote
1answer
63 views
A neural network for digits recognition doesn't work (MNIST, Numpy) [closed]
I'm a beginner in machine learning and I was trying to make a test neural network for digits recognition from scratch using Numpy. I used MNIST dataset for training and testing. Input layer have 28*28 ...
3
votes
0answers
15 views
Batch PTA stopping condition
I am reviewing my Neural Network lectures and I have a doubt: My book's (Haykin) batch PTA describes a cost function which is defined over the set of the misclassified inputs.
I have always been ...
2
votes
0answers
73 views
Non-monotonic activation function and XOR problem with perceptron
I already post the question on Stackoverflow : https://stackoverflow.com/questions/53785922/is-the-use-of-a-non-monotonic-activation-function-is-a-correct-and-viable-solut?noredirect=1#...
4
votes
6answers
236 views
Why can't the XOR linear inseparability problem be solved with one perceptron - like this?
Consider a perceptron where $w_0=1$ and $w_1=1$:
Now, say we use an activation function
$f(x)=1,~for~x=1$$~~~~~~~~~~~~~0, otherwise$
The output is then summarised as:
$x_0~~~~~x_1~~~~~w_0*x_0 + ...
1
vote
0answers
52 views
First perceptron learning algorithm
I struggle to find Rosenblatts perceptron training algorithm in any of his publications from 1967 - 1951, namely:
[1] Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms
[2] ...
5
votes
1answer
87 views
How does a single hidden layer neuron affect output?
I'm learning about multilayer perceptrons, and I have a quick theory question in regards to hidden layer neurons.
I know we can use two hidden layers to solve a non-linearly seperable problem by ...
0
votes
1answer
47 views
Update theta in a perceptron?
Is theta supposed to be updated in a perceptron, like the weights, and if so, what is the formula for this?
I'm trying to make the perceptron learn AND and OR, but without updating theta, I don't ...
4
votes
2answers
141 views
Is a Multilayer Perceptron a recursive function?
I read somewhere that a Multilayer Perceptron is a recursive function in its forward propagation phase. I am not sure, what is the recursive part? For me, I would see a MLP as a chained function. So, ...
1
vote
1answer
76 views
Minimum number of perceptrons for an n-bit truth table?
Suppose I have a Boolean function that maps N bits to one bit. If I understand correctly, this function will have 2^2^N possible configurations of its truth table.
What is the minimum number of ...
1
vote
2answers
149 views
Creating a working perceptron
I'm trying to learn more about AI by trying to program a neural network. First I'm trying to understand writing my own perceptron but I'm struggling to get a basic perceptron working correctly.
I've ...
4
votes
2answers
515 views
Perceptron learning algorithm: different accuracies for different training methods
So, my question is a bit theoretical. I have been trying to implement a perceptron based classifier with outputs 1 and 0 depending on the category. I have used 2 methods: The ...
2
votes
1answer
189 views
Understanding the perceptron algorithm in the book “A Course in Machine Learning”
The following text is from Hal Daumé III's "A Course in Machine Learning" online text book (Page-41).
I understand that $D$ is the size of the input vector $x$.
What is $y$? Why is it introduced in ...
