Questions tagged [multilayer-perceptron]

For question about Multi Layer Perceptron model/architecture, its training and other related details and parameters associated with the model.

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Backpropagation equation for a variant on the usual Linear Neuron architecture

Recently I encountered a variant on the normal linear neural layer architecture: Instead of $Z = XW + B$, we now have $Z = (X-A)W + B$. So we have a 'pre-bias' $A$ that affects the activation of the ...
75 views

Which online machine learning technique to use for multi-class classification problem with multiple inputs?

I have the following problem. We have $4$ separate discrete inputs, which can take any integer value between $-63$ and $63$. The output is also supposed to be a discrete value between $-63$ and $63$. ...
83 views

How to deal with padded inputs in a fully connected feed forward network?

I have a fully connected network that takes in a variable length input padded with 0. However the network doesn't seem to be learning and I am guessing that the high number of zeros in the input ...
43 views

Recent algorithms for correcting mislabeled data using multilayer perceptrons

I am doing literature research on algorithms for correcting mislabeled data using multilayer perceptrons. Found an "old" paper An algorithm for correcting mislabeled data (2001) by Xinchuan Zeng et al....
93 views

Is there a mathematical theory behind why MLP can classify handwritten digits?

I'm trying to really understand how multi-layer perceptrons work. I want to prove mathematically that MLP's can classify handwritten digits. The only thing I really have is that each perceptron can ...
60 views

How I can predict the next number in a sequence with a neural network?

I've been dabbling with machine learning and neural networks (namely, resnet50) for a few months now, mostly doing image recognition. I am currently trying to make a program that, given a string of ...
168 views

Unable to overfit using MLP

I'm building a 5-class classifier with a private dataset. Each data sample has 67 features and there are about 40000 samples. Samples of a particular class were duplicated to overcome class imbalance ...
25 views

How can I adapt this script (to test the robustness of a perceptron) to test the robustness of a multi-layer perceptron?

The following script is from Trappenberg's Fundamentals of Computational Neuroscience and is used to test a perceptron's robustness against noise. However, how would one alter it to test the output ...
23 views

Model unfit for some part of spiral data despite low error

I'm current testing a model for spiral data. After 500 epoches, loss is 0.04 but the result is still unmatch with some part of the training data. (bottom left) The model has 2 hidden tanh x 16 units ...
28 views

Does a varying ANN model accuracy mean underfitting or overfitting?

Background: This is for a simulated robot with four legs, walking on a flat terrain. The ANN (an MLP) is given inputs as the robot's body angle, positions and angle of each leg with respect to the ...
26 views

Applying Machine Learning to 2D Laser Scanner Data

We are using 2D Laser Scanner to scan various objects of different geometric shapes for e.g. cylinder, spiked, cylinder with notch, cylinder with curved edges e.t.c. The dataset contains points in the ...
46 views

Is there data available about successful neural network architectures?

I am curious to if there is data available for MLP architectures in use today, their initial architecture, the steps that were taken to improve the architecture to an acceptable state and what the ...
54 views

How can an ANN efficiently predict multiple numbers with fixed sum (in other words, proportions)?

I need a neural network (or any other solution) to predict 3 values which sum equals a fixed number (100). This will help me calculate proportions. Which is the most efficient way to do this? The ...
209 views

Sigmoid output layer and Cross-Entropy cost function

I use Sigmoid activation function for neurons at output layer of my Multi-Layer Perceptron also, I use cross-entropy cost function. As I know when activation functions like Tanh is used in output ...
26 views

What is the purpose to have fully connected layers?

What is the purpose of a fully connected multi layer perceptron in which every input is connected to every output by a weight? After all, the information is only distributed over several channels, but ...