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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MLP local minima question

I came across an excercise on deep learning from here. It goes as follows: Consider a simple MLP with a single hidden layer of $d$ dimensions in the hidden layer and a single output. Show that for any ...
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Developing Custom MLP for Mnist

I am trying to develop a custom MLP for MNIST Dataset with 2 hidden fully connected layers Mnist: 28281 FC1: input 28*28, output 512 FC2: input 512, output 128 Classifier: FC: input 128, output 10 I ...
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SHAP for Deep Neural Network taking long time

I have 60,000 samples with each having 1,800 features. I have made a multilayer perceptron in Keras and I want to use SHAP values to arrive at global feature importance. Is the matrix too big for SHAP?...
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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 ...
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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 ...
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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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Why we use an activation function for introducing nonlinearity instead of a polynomial Perceptron implementation?

I perceive a single perceptron as a single linear function $y = a_1x_1 + a_2x_2 + ... + a_nx_n + b_0$ with a goal to calculate the best weights combination $ w_1, w_2, ..., w_n $ that minimizes the ...
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30 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, ...
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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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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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235 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 ...
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Lower training accuracy than testing accuracy (MLP/Dropout)

I am working on a problem of multi-class classification by MLP. I have set dropout to each middle layer. Now I observe the training accuracy is around 10% less than ...
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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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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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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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28 views

How to structure the output layer of an MLP that finds the quadrant of an arbitrary point in a rectangle?

I'm trying to write a neural network that outputs the quadrant of a rectangle that an arbitrary point lies in. This rectangle has its upper left at {0, 0} and its lower right at {1, 1} (e.g. point {0....
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implementing forward and backward of a Linear model

I'm implementing the code of this abstraction. The forward is easy and looks like that: I don't understand the backward path and how it fit's the abstraction in the first image: Why is db defined as ...
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162 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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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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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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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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159 views

keras how to subset input in Model

I have a data of the following format: ...
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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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418 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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576 views

(De-)Scaling/normalizing input and output data inside Keras model as layer

I am building a 2-hidden layer MLP using Keras. I'm using a SciKit learn wrapper to be able to use the GridSearchCV functionality. My sample-size is limited, ...
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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 ...
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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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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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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: ...
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Logistic Regression outperforms MLPClassifier

I am new in ML and I am trying to train classifier. I have a tiny dataset, just 90 examples, I divided it 70/30 train/test set and started to train. As I know MLP must outperform Logistic Regression, ...
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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 ...
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Is it possible to decompose a scalar value to a inter-dependent vector neural network?

My data contains a scalar feature $r$, I found this feature is important for training my deep model. My idea is supposing there is a 3-layer MLP $f(x), x \in \mathbb{R}^{n}$, where $n=1$. It outputs a ...
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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 ...
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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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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 ...
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1answer
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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 ...
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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 ...
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125 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 ...
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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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Getting different precisions for same neural network with same dataset and hyperparameters in sklearn mlp classifier

I get WAY DIFFERENT results in each run despite using random state for making sure that network outputs same result for same hyper parameters, here is some sample outputs(I've printed the hyper ...
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756 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,...
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116 views

What does it mean when an Actual vs Predicted plot is like this assuming you are using the best model?

I'm trying to predict the monetary value in a fixed time-frame for a project. I wanted to start with a baseline model before doing any feature engineering or advanced pre-processing. I'm using a feed-...
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174 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 ...
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170 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 ...
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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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131 views

Keras MLP Classifer Model not converging

I'm trying to make MLP based classifier based on numerical and categorical data The train_X (Input) data that I'm working with is look like that each data type is 20 numerical and 1 categorical ...