Questions tagged [mlp]

MLP stands for multi-layer perceptron, the most basic kind of neural network. Also called DNN (deep neural network), as opposed to CNN or RNN (convolutional and recurrent neural networks).

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13
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2answers
49k views

How to adjust the hyperparameters of MLP classifier to get more perfect performance

I am just getting touch with Multi-layer Perceptron. And, I got this accuracy when classifying the DEAP data with MLP. However, I have no idea how to adjust the hyperparameters for improving the ...
8
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4answers
135 views

How to handle features which are not always available?

I have a feature in my feature vector that is not always available respectively sometimes (for some samples) it makes no sense to use it. I feed a sklearn MLPClassifier with this feature vector. Does ...
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2answers
969 views

What is the difference between multi-layer perceptron and generalized feed forward neural network?

I'm reading this paper:An artificial neural network model for rainfall forecasting in Bangkok, Thailand. The author created 6 models, 2 of which have the following architecture: model B: ...
5
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1answer
181 views

Can a neural network recognize a letter B as an A if your trained it so?

You have a neural network. And you have, say, pictures of $100,000$ hand-written letters (A-Z). Now you make a typical Training and the neural network will recognize an A as an A, a B as a B, ... Now ...
4
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2answers
10k views

How do I get the feature importace for a MLPClassifier?

I use the MLPClassifier from scikit learn. I have about 20 features. Is there a scikit method to get the feature importance? I found clf.feature_importances_ but it seems that it only exists for ...
3
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1answer
253 views

Why would one crossvalidate the random state number?

Still learning about machine learning, I've stumbled across a kaggle (link), which I cannot understand. Here are lines 72 and 73: ...
3
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1answer
339 views

Why does the MAE still remain, at all?

This may seem to be a silly question. But I just wonder why the MAE doesn't reduce to values close to 0. It's the result of an MLP with 2 hidden layers and 6 neurons per hidden layer, trying to ...
3
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1answer
131 views

Understanding computations of Perceptron and Multi-Layer Perceptrons on Geometric level

I am currently watching amazing Deep Learning lecture series from Carnegie Melllon University, but I am having little bit of trouble understanding how Perceptrons and MLP are making their decisions on ...
3
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1answer
90 views

How to utilize user feedback due to miss-classification when correct class label is unknown?

Suppose we are developing an app which is supposed to predict a dog's breed by it's picture. We trained a classifier (in my case an MLP) using some dataset and shipped the app to users. Now suppose ...
3
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1answer
50 views

Coding MLP: good practices?

I recently finished coding my own MLP neural network in Python. To make my code easier to read, I separated the MLP, into classes; the network class, the layers class and the neuron class, where the ...
3
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2answers
167 views

Geometric interpretation of MLP output

I am really interested in the geometric interpretation of perceptron outputs, mainly as a way to better understand what the network is really doing, but I can't seem to find much information on this ...
3
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2answers
2k views

Adding more layers decreases accuracy

I have my ANN trained on MNIST dataset. Hidden layer has 128 neurons and input layer has 784 neurons. This gave me an accuracy of 94%. However when I added one more layer with 64 neurons in each then ...
3
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1answer
42 views

Alternatives to regression to decide weights in an expression

I have a use case in which I am required to predict variable $y$ which depends on five variables $x_i$. Consider something like $$ y=w_1 x_1+ w_2 x_2+ w_3 x_3+ w_4 x_4+ w_5 x_5.$$ This expression ...
3
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1answer
60 views

Neural Network regression negative performance

I have a problem with the performance of a multi layer perceptron regressor (neural network) and I cannot figure out why. Task: I am trying to improve a time series prediction. I have predictions of a ...
2
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2answers
82 views

how to access weights of individual Neurons in the output layers in MLPs?

im working on a neural network using Keras. Its an mlp(multi-layer perceptron). With 8 Neurons in the output layer. Is there a way I can access weights and biases of individual neurons of the output ...
2
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1answer
120 views

Conceptual questions on MLP and Perceptrons

I am facing some confusion regarding the terminologies assocaiated to classification and regression problems esp. using the MLP and Perceptron models. These are the following: 1) When the data is ...
2
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3answers
247 views

How each layer of a neural net is responsible for one feature

Through my study of neural networks, I came across the idea that each layer of a neural network is responsible for recognizing one feature of the input data. For example, if we build a neural network ...
2
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2answers
155 views

Neural Network Hidden Layer Selection

I am trying to build an MLP classifier model on a dataset containing 30000 samples and 23 features. What are the standards I need to consider while selecting the ...
2
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1answer
55 views

Scikit model is not able to predict sequence correctly

I am trying to create a regression model using scikit-learn for predicting car price. The input data are, car model(trim), kilometers used, past resale price of similar car and age of used car. I am ...
2
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2answers
809 views

Why might a neural network consistently underestimate its target?

I have a neural network (MLP) that is consistently underestimating the target variable on the validation set, test set, and on the training set (by about the same amount as on the validation set and ...
2
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1answer
473 views

Is the multilayer perceptron only able to accept 1d vector of input data? If yes, why is this so?

I am going through the tutorial at the link below which uses MNIST handwritten digit database. https://machinelearningmastery.com/handwritten-digit-recognition-using-convolutional-neural-networks-...
2
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2answers
5k views

MLPRegressor Output Range

I am using Scikit's MLPRegressor for a timeseries prediction task. My data is scaled between 0 and 1 using the MinMaxScaler ...
2
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1answer
24 views

avoiding premature convergence with neural networks (EA's)

I am currently writing a program that would be able to play snake on an 25*25 grid. It works by optimizing a set of weights of 300 different solutions (each solution would be a different neural ...
2
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1answer
46 views

SciKit Learn: Multilayer perceptron early stopping, restore best weights

In the SciKit documentation of the MLP classifier, there is the early_stopping flag which allows to stop the learning if there is not any improvement in several ...
2
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3answers
90 views

About different structures of neural network

https://www.mathworks.com/help/deeplearning/ref/fitnet.html is the tutorial that I am following to understand fitting data to a function. I have few doubts regarding structure and terminologies which ...
2
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1answer
141 views

Interpreting MLP output

I just wrote an MLP in Python. After having trained it, I pass in some test data to see the result, and I get an array of decimal numbers at the output, rather than the desired binary output. For ...
2
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1answer
17 views

Training loss stuck in the starting epochs but then starts decreasing. What could be the reason for it?

I am training a model where I found a unique problem that for starting 4 epochs, my loss did not change with the epochs but after that, it started changing. Could it be because of the high learning ...
2
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1answer
161 views

How to understand what each layer is learning in a Deep learning neural network?

In a recent answer I read on Stack Exchange, I read about a possible way to understand more clearly what happens in each hidden layer of a neural network. Here's the excerpt- You should watch ...
2
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0answers
84 views

Pruning for multi-layer perceptron

Here, I have the single hidden layer multi-layer perceptron (Input: 4 units, hidden unit: 3 units, output: 1 unit). I want to do pruning before a training process with Keras. Concretely, I just want ...
2
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1answer
1k views

multilayer perceptron do not converge

I have been coding my own multi layer perceptron in MATLAB and it can be compiled without error. My training data features,x, has values from 1 to 360, and training data output, y, has the value of ...
2
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2answers
489 views

MLP conv layers

When should MLP conv layers be used instead of normal conv layers? Is there a consensus? Or is it the norm to try both and see which one performs better? I would love to better understand the ...
1
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3answers
384 views

Are weights of a neural network reset between epochs?

If an epoch is defined as the neural network training process after seeing the whole training data once. How is it that when starting the next epoch, the loss is almost always smaller than the first ...
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3answers
1k views

More layers in NN give worse result

So I was working on a classification task with the help of a NN. The data-set was normalised, weights random between 0-1, and all the activations were sigmoid ...
1
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1answer
50 views

Different hidden layer architectures deliver the same classification results, is that normal?

I have a data set with 600 data points with about 10 attributes (binary). The dataset has been normalized: Xnormalized = StandardScaler().fit_transform(X) The ...
1
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1answer
742 views

MLP Parameter tuning - gridsearchCV cannot fit?

I'm making an MLP classifier for binomial classification from 145 features. I want to get the best parameters on my MLP classifier to get a better prediction so I followed the answer to this question,...
1
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2answers
298 views

Why is the reported loss different from the mean squared error calculated on the train data?

Why the loss in this code is not equal to the mean squared error in the training data? It should be equal because I set alpha =0 , therefore there is no regularization. ...
1
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1answer
500 views

IN CIFAR 10 DATASET

After building up the mlp using ...
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3answers
441 views

One Hot Encoding of Age

My task is to predict how many years a person has left to live using an MLP. There is one specific feature I'd like to discuss: current age. Statistically, it's a conditional probability. Example: ...
1
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1answer
26 views

Is a multi-layer perceptron exactly the same as a simple fully connected neural network?

I've been learning a little about StyleGans lately and somebody told me that a Multi-Layer Perceptron, MLP, is used in parts of the architecture for transforming noise. When I saw this person's code, ...
1
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1answer
176 views

What are the differences between MLP and DNN?

So I have been reading about the topic for a while, but i did not find a clear answer why MLP and DNN are being used interchangeably even though there are some differences between them. So far I have ...
1
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1answer
57 views

Why is my MLP with 2 features is doing worse than MLP with 1 feature where the one feature is a combination of feature1*feature2?

I have programmed a MLP for a dataset (~500 rows) containing the length (L) and width (W) of an organism and the output of biomass (the organisms weight in pounds, B). ...
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2answers
142 views

Input data of variable length - two scenarios

I'm trying to figure out how I could train a neural network with inputs that have variable length. This issue comes up in the following 2 scenarios I'm trying to solve. Scenario 1: I have a long list ...
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2answers
113 views

Data pre-processing before feeding into a deep learning model

Generally speaking, when training a deep learning model, like MLP, what kind of data pre-processing operation has to be conducted when the input is a numerical sequence.
1
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1answer
562 views

Polynomial regression vs. multilayer perceptron [closed]

Polynomial regression and multilayer perceptrons have different structures and different learning procedures. What are these two algorithms pros and cons? Are there some situations where one should ...
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1answer
16 views

Input changing row count matrices in an MLP

I want to input a numpy 2d array into MLP but I have an array of 50395 rows that contains many 2d array of shape (x, 129). x ...
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0answers
11 views

model tuning by using loss curves

I have been practicing with the following dataset: http://archive.ics.uci.edu/ml/datasets/Concrete+Compressive+Strength for building a prediction model based on a MLP, but I have some doubts if the ...
1
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2answers
554 views

Feature scaling for MLP neural network sklearn

I am working with a dataset that has multiple scales for my features. Before running sklearn's MLP neural network I was reading around and found a variety of different opinions for feature scaling. ...
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0answers
14 views

Which MSE (total or individual) back-propagate for multi out regression neural network

When we have multi output regression neural network, we can calculate total MSE and individual MSE per output. How this MSE should back-propagate ? Shouldn't we back-propagate individual MSE through ...
1
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1answer
26 views

Structuring experiment/training data with months in mind

We're using a whole year's data to predict a certain target variable.The model works like data - OneHot encoding the categorical variables - MinMaxScaler - PCA (to choose a subset of 2000 components ...
1
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1answer
26 views

LabelEncoder with a Multi-Layer Perceptron?

So we're working on a machine learning project at work and it's the first time I'm working with an actual team on this. I got pretty good results with a model that uses the following SKLearn pipeline: ...