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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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 ...
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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 ...
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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 ...
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1answer
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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 ...
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2answers
485 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 ...
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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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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 ...
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2answers
541 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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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 ...
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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 ...
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108 views

Help with MLP convergence

I posted this question on AI SE and got advised to ask here for guidance. I've been stuck for a couple of days trying to figure it out how the standard MLP works and why my code doesn't converge at ...
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1answer
94 views

What are the key differences between a MLP with lagged features and a RNN

I've been working with MLP's for a while. Whenever I assumed that the past values of a feature might be useful for predicting the future values of Y, I would just create a new column in my data frame ...
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28 views

Minimizing Costfunction in a Feedforward MLP

I made a sweep on a feedforward MLP changing number of layers and neurons per layer, in order to see an effect on the costfunction. Costfunction = 0.5 (Trainingoutput - Modeloutput)^2. For the ...
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Multidimensional Output from Radar Imagery and Climate Data

I am trying to predict what my rainfall field will look like at a future timestep using: Radar imagery of rainfall fields at previous timesteps: A set of 2D matrices where each element in each matrix ...
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How to implement Multi Layer Perceptron in Keras

I am trying to implement the network in the paper Two-Stream Deep Feature Modeling for Automated Video Endoscopy Data Analysis available here. However, I am confused about the Multi layer Perceptron ...
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29 views

Tensorflow V1, tf.global_variables_initializer() got error: InvalidArgumentError: feed a value for placeholder tensor 'X'

I have started learning Tensorflow V1, and try to implement a 4-layer MLP model with Batch Normalization. But once I invoke the BN() function into the model, it will report ...
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1answer
151 views

MLP classifier Gridsearch CV parameters to tune?

I'm looking to tune the parameters for sklearn's MLP classifier but don't know which to tune/how many options to give them? Example is learning rate. should i give it[.0001,.001,.01,.1,.2,.3]? or is ...
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Sparse data and Neural Networks

I am trying to learn a model to predict the binary outcome of a computer game. The input data consists of the character picks by each of the ten players (two teams of 5, 150 possibilities each, with ...
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142 views

keras how to subset input in Model

I have a data of the following format: ...
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152 views

Am I doing bayesian optimization correctly for MLP?

I am trying to optimize the below mentioned hyper-parameters of MLP with range as follows. Number of hidden layers (n): 1-10 Number of perceptrons (p): 25, 50, 75, ..., 200 Activation function: ...
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38 views

NLP Word ordering problem in Keras

I'm trying to solve the word ordering task: given a syntactically unordered sentence, recover the right order of the words. The adopted approach is to transform each sentence in a dependency tree and ...
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38 views

can i get weights per iteration of MLP?

im building an mlp with scikit learn. Is there a way I can access weights and biases of the output layer per iteration? There is an option mlp.coefs_ But it ...
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101 views

Deep learning(MLP) on multiclass classification. Model learns only one class

I am new to deep learning. I have imbalanced class data. I used one hot encoding and scaling to preprocess my data. I have used adamoptimizer as optimizer function and sparse categorical crossentropy ...