All Questions
10 questions
0
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58
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Is it possible to predict non-classifiable label using single layer perceptron and sigmoid function? (without using any perceptron library)
Imagine predicting BMI index like 1,2,3,4,5 and having weight and height as input. I know it can be easily done with other method. Also I have to use sigmoid function and I am really new to this. I ...
1
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0
answers
160
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How can I explain the difference in decision boundary and its reason in relation to the dimension of the hidden layer?
I got these 3 different plots of decision boundaries using 3 different parameters for hidden_layer_sizes of the MLPClassifier from sklearn on XOR gate.
...
- 21
2
votes
1
answer
244
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How to resolve the perceptron dilemma for binary classification?
I have a following thought problem involving perceptron and binary classification that I wonder if anyone has thought about before. This is not from any textbook or reference, although I doubt I'm the ...
- 734
1
vote
0
answers
98
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Rule of thumb for Data Requirements when Designing a Neural Network for Deep Learning
I'm designing an MLP classifier and I've been noticing that:
Using a very shallow network, or one whose at least one layer has a small number of neurons yields bad performance
Using a deep network ...
- 111
5
votes
2
answers
3k
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Why perceptron is linear classifier?
It is said that perceptron is linear classifier, but it has a non-linear activation function f = 1 if wx - b >= 0 and f = 0 otherwise
If i will use some non-linear function on linear combination of ...
- 71
0
votes
0
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73
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Choosing perceptron weights to achieve 0% error
I'm really not sure what to do for this question, although I think I would be able to do q3 if I knew how to do q2
user243609
4
votes
1
answer
1k
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Neural Networks - Difference between one dimensional layer vs multi-dimensional layer
Please take a look at these Neural Network architectures:
I can understand the architecture of Hidden Layer in Net-2 : you add 12 Neurons to your hidden layer...
What I can't understand is the 2-...
- 515
0
votes
1
answer
2k
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SLP vs. MLP: Is my data linearly separable?
I implemented an artificial neural network using scikit neuralnetwork. As default configuration for my classification task I am using
10730 Datsets x 115 Features
1 Hidden Layer with 61 neurons
7 ...
- 103
1
vote
0
answers
544
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Why use a restricted Boltzmann machine rather than a multi-layer perceptron?
I'm trying to understand the difference between a restricted Boltzmann machine (RBM), and a feed-forward neural network (NN). I know that an RBM is a generative model, where the idea is to reconstruct ...
- 7,129
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