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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330 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 ...
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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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1answer
27 views

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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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 ...
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1answer
16 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 ...
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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, ...
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1answer
140 views

How Does Sci-Kit Learn Train Regression Neural Networks (MLPRegressor) So Fast?

Why does using the scikit-learn library's MLPRegressor result in such a boost in training time when compared to constructing the network from scratch? I tried both methods and I found that writing the ...
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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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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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13 views

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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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 ...
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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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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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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.
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16 views

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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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 ...
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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 ...
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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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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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1answer
236 views

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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1answer
169 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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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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1answer
17 views

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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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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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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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 ...
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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 ...
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1answer
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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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 ...
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1answer
50 views

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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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 ...
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1answer
140 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 ...
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28 views

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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3answers
380 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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1answer
542 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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0answers
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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1answer
98 views
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1answer
141 views

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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1answer
110 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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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 ...
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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 ...
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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: ...
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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 ...
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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. ...
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1answer
39 views

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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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 ...
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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 ...