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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Question about MLP and CNN

Can I use a MLP model architecture for taking a dataset with more than 10 features which are correlated to each labeled video frame along with a CNN that takes in solely the labeled video frame to ...
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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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24 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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37 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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80 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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8 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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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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30 views

keras how to subset input in Model

I have a data of the following format: ...
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Which values should i use as data for this Weka problem?

I have a problem that has to be translated into an ARFF file. We have a robot that has to reach X without going to the black squares. It can go up, down, left, right, or stay to its position. These ...
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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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107 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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141 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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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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14 views

Understanding usage of dropout in Keras

I would like to check if my understanding of how dropout layers should be used in Keras training is correct. I am training pretty simple MLP regression models: ...
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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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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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101 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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27 views

How to define the right range values for learning rate, epochs, batch size and hidden layers in a neural network

Well, these last days I am focusing more on developing some experiments with MLP and after CNN neural networks to a paper, here when I was running the experiments I realized that only if I put 0 in ...
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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
47 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 ...
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68 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
68 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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478 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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Test set error significantly less than training set error

I am trying to model an decoder(for specifics of it, refer to the details below) using a MLP. But I am getting strange results. Metric being used here is the bit error rate (ber). My training set and ...
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73 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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1answer
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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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136 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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72 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 ...
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1answer
88 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 ...
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244 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: ...
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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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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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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 ...
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218 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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121 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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265 views

IN CIFAR 10 DATASET

After building up the mlp using ...
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118 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 ...