All Questions
Tagged with neural-network keras
648 questions
2
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41
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Image-to-Image with U-Net no Skip-connections. Is it real?
In general, U-Net is needed to create another style image, but preserve the structure. For example, a full-fledged drawing from a sketch. Right?
I want to preserve the style, but change the structure. ...
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0
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1
answer
23
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Why does tanh activation work better with Pytorch than with Keras?
I'm doing a neural network to recognize written Cyrillic letters, and I found out that, when I use tanh activation function, it works WAY better with PyTorch than with Keras.
Keras code:
...
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1
vote
1
answer
112
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Where has RSquare from tensorflow_addons.metrics gone and what's the appropriate replacement in model.compile(…) of keras?
tensorflow_addons is dead:
...
- 121
1
vote
0
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47
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Why can't I replicate the results from this paper?
I'm trying to train a model to evaluate chess positions, following the methodology from this paper (note that the author presents several different architectures, but I'm only looking at the ANN with ...
0
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1
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136
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Is it possible to train a neural network to feed into a Random Forest Classifier or any other type of classifier like XGBoost or Decision Tree?
I want to create a model architecture to predict future stock price movement as such:
The Goal of this model is to predict if the price will go UP or DOWN within the next 3 months.
I have tried a few ...
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0
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0
answers
10
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Overfitting - Imbalance Classification using Deep-feed forward network
I have an unbalanced dataset, so I used SMOTEENN on the training set to resample, after training DFF,i could see the model is overfitting, could someone help me solve this?
Thank You.
...
0
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0
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59
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Tensorflow SegNet architecture
I was unable to find a complete description of the SegNet architecture for image segmentation (specifically, the decoder layers). Therefore, I would like to clarify the correctness of my ...
- 51
1
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1
answer
62
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Does using different optimizer change the loss landscape
I plot the landscape using this code, and I notice the landscape shape has changed a lot. My understanding is that the optimizer does not change the loss landscape. But now I'm confused if its just ...
- 127
0
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1
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60
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How do I ensure final output shape matches input shape for a semantic segmentation task?
I trying to replicate the semantic segmentation example
https://keras.io/examples/vision/oxford_pets_image_segmentation/
but train on my own data. I have 8 labels (7 features + background). My images ...
0
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0
answers
10
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Using a neural network to predict disease outcomes in individual cases
I'm working on a research project with the goal of using a neural network to predict disease outcomes for patients. I've built a neural network using Tensorflow and Keras and I've trained and tested ...
0
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1
answer
84
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Connecting Flatten layer to Dense layer
I'm struggling with my neural network.
In short, I need to recreate a model from anywhere on the internet, I've found a model that combines BiLSTM, LSTM and GRU. However, based on the error I got when ...
0
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1
answer
47
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My custom neural network is converging but keras model not
in most cases it is probably the other way round but...
I have implemented a basic MLP neural network structure with backpropagation. My data is just a shifted quadratic function with 100 samples. I ...
0
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1
answer
37
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What exactly is saved when I save a NN?
After we trained a Neural Network, we can save it in order to be able to predict without re-training. So when we use model.save('my_model.keras') what exactly is ...
- 163
0
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0
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22
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Neural network does not overfit my data. (Primarily linear function)
I am using TensorFlow and Keras. My goal is to approximate a primarily linear function that is partially nonlinear, such that a linear regression yields a Mean Absolute Error (MAE) of 0.13. All ...
0
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0
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27
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Keras DNN outputs the same value over and over
I'm creating an ensemble of NNs with the same architecture, but each NN only outputs one value when given X_test data. The data (continuous values transformed to be [-1,1]) yields results as expected ...
1
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1
answer
58
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How to balance labeled datas and then carry out execution with a certain ratio?
I'm building a binary classification model using a neural network, with python and the libraries tensorflow and keras.
For that I have an unequal amount of labeled data: Around 2'000'000 labeled with <...
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0
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0
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22
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Why isn't the validation data loss close to the test data loss?
First I set aside about 15% of my data as test data. Then, I used tensorflow.keras to create a relatively simple neural net model. Then I set the model.fit() parameter validation_split=0.2, so 20% of ...
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2
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1
answer
133
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Why the test accuracy showing some odd behaviour in comparison to train accuracy?
I am currently training an ANN using Sequential(a class from Keras API within tensorflow), and I am optimizing the model's architecture and came across something I have not seen before.
The graph of ...
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1
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1
answer
220
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activation=tf.keras.activations.relu vs activation='relu'
Both models are for binary classification problems
Model 1
...
0
votes
1
answer
101
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Confusion with tensorflow's Sequential Dense Layers
I'm working on a regression probem using Tensorflow, and have created two models with slight differences in their first Dense layer.
The Models
...
0
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1
answer
115
views
Neural Network for binary classification not working
I have made a neural network that was working correctly as a multi-class classifier, but after changing the loss and the activation function, plus the output layer to just 1 neuron, it is not working ...
0
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1
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148
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Custom Loss Function in Tensorflow for UNet
I am working on a Segmentation task, where I planned to use U-Net
for the input_image of shape (224,224,3), the output should be the mask image of shape ...
- 21
1
vote
1
answer
44
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Patterns binary classification - model doesn't overfit
I am working on a very basic binary classification problem. For each set of four float numbers $(x,y,z,w)$, I want to check if they fall or not into one category.
I have written a model in Keras with ...
- 121
0
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1
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76
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Very low Neural Network Accuracy for Titanic Survival Problem
I am new to neural networks and have done a few projects but have got very low accuracy for all of them. I have included the code for titanic NN code here. Am I missing something or what? Can you help ...
1
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1
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73
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How to align the description of a convolutional neural network in keras with wikipedia's conceptual model?
I was going through the introductory guide to convolutional neural networks in tensor flow here
And I was trying to logically map some of the code I saw to my actual understanding of how convolutional ...
- 111
1
vote
0
answers
55
views
Generator loss keeps increasing while discriminator keeps decreasing
I am trying to build a GAN to generate LEGO images however my generator is not working at all. I have tried changing the learning rates but it caused the loss to go even more higher, sometimes into ...
0
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0
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97
views
I have a strange loss behavior in Tensorflow/Keras. It goes smooth towards better values, and then suddenly it increases rapidly before falling again
I have a model that trains on a dataset of 100000 data points. The model is a single dense layer with a single neuron.
During training, I use a batch size of 1000 and train for 250 epochs. After ...
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0
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1
answer
580
views
What preprocessing should I do to a multiclass segmentation mask?
I am working on a segmentation problem. My masks are tensors with a shape of (4767, 192, 192, 1) --> (num_img, height, width, number of channels). Each mask contains 13 different pixel values (0, 1,...
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1
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1
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61
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What should I Improve from my Neural Network Model (Logistic Regression)
Initial Information
I built a Neural Network Model (Logistic Regression) to classify Lung Cancer based on the patient's (user) symptoms
My dataset is kind of small (only about 276 data)
Here is the ...
- 11
1
vote
1
answer
172
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How to correct ValueError about incompatible dimensions of training data set in locallyconnected1D layer NN
I'm training this simple network with a few points, but it can't train. The model looks okay, but when training it raises a ValueError about the dimension of the training data sets. Could someone help?...
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0
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1
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562
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How to use Keras Sequential with LocallyConnected layers
enter image description here
I am trying to use locally connected neural networks to estimate finite elements of a mathematical function, using the Keras Sequential model. When I use dense layers all ...
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0
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1
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443
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Can I change the number of inputs to a keras model while preserving the trained existing weights
I have a simple Sequential keras model with 150 Inputs.
Some of these are simply OneHotEncoded values. Now I would like to add more options to the OneHotEncoder.
As an example: I previously had Blue, ...
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0
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1
answer
529
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Tensorflow / Keras - Using both ModelCheckpoint: save_best_only and EarlyStopping: restore_best_weights
ModelCheckpoint
save_best_only: if save_best_only=True, it only saves when the model is considered the "best" and the latest best model according to the quantity monitored will not be ...
- 21
0
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1
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99
views
A curve val_loss and loss in keras after training a model
Can anyone help me, is my model overfitting or underfitting?
I want to make sure the model is well done before starting to deploy
Also, I use categorical cross-entropy loss
I have asked before, but I ...
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-1
votes
1
answer
103
views
Curve val_loss and loss in keras after training a model
I trained a Keras model to diagnose disorders and want to make sure it is good enough to start deploying.
From the below graph, can anyone advise me as to whether my model is overfitting or ...
0
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0
answers
3k
views
ValueError: Input 0 of layer "model_12" is incompatible with the layer: expected shape=(None, 256, 256, 3), found shape=(256, 256, 3)
I am following this keras example with my own dataset, which has 3 classes. I load the images using
...
- 103
1
vote
1
answer
425
views
Regression to fill NA values
As a part of an exercise, I have the following dataset. Note that I have no idea where the values come from (are they based on something real or are they random numbers? Don't know...)
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- 111
1
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1
answer
1k
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How to compare $R^{2}$ of train and test data in a Deep Learning Neural Network Regression model?
I want to judge the goodness of my neural network regression model built using Keras Python Library. The problem is the following: from an input like (1000, 5000) so 1000 samples and each sample has ...
0
votes
1
answer
1k
views
Keras: LSTM model training - great differences in training results
This is an issue I've been encountering before and I was wondering what can be potential causes for this. Occasionally, training of an identical setup LSTM model ( using Keras ), on the same training ...
- 101
0
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1
answer
194
views
Difference between class_weight and loss_weights arguments in TensorFlow/Keras
I am creating a neural network using TensorFlow (v2.9.2) for an imbalanced image dataset. While doing so, I noticed that model.compile() method has an argument <...
- 87
0
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0
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314
views
CNN-BERT Text Classification good results on train and val, but bad prediction on testing
I built a Keras model to predict hoax news and true news using the CNN-BERT Text Classification algorithm with Categorical Classification, with label 1 indicating a hoax and 0 indicating true news.
...
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1
vote
1
answer
265
views
No improvement in test and training accuracy when training different optimizers
I am currently testing 5 different optimizers to see their training loss, and their testing accuracy. The optimizers are: AdaGrad, AdaDelta, RMSprop, Adam, Nadam. I am using a quite simple model with ...
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1
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0
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273
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Keras NLP TransformerDecoder MultiHeadAttention Value Error
Recently I have been working on a MIDI Music Generator using the TransformerEncoder & TransformerDecoder layers found in the Keras NLP library. There is not much info/help on these layers which is ...
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1
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0
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31
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What is exactly the loss value evaluated at every epoch of training?
If I compile a certain model with adam optimizer and I have used a batch size of 32 in the fit function, When I start training the model, I get a loss value at the end of every epoch. I understand ...
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0
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1
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35
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Is this a case for too much dimensionality? 1881 samples, 2562 features
I have been working on creating a multi-class classification model for medical data. I have 1881 samples, 2562 features each, and 6 classes total. My distribution of classes is as follows:
{1: 83, 2: ...
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1
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1
answer
35
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Modelling Player Impact on English Premier League
Let's say you have a very wide feature vector, all 0s and 1s, all 500 players in Premier League as features, out of which only 22 participate in a match. Those that participate are marked with 1s, ...
3
votes
1
answer
793
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Should I use validation data and val_loss when training final model?
I am training a keras model that utilizes early_stopping in order to prevent overfitting. This requires that I set aside a validation dataset.
My task requires that ...
- 133
0
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1
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1k
views
TypeError: object of type 'NoneType' has no len() when implementing neural network
I am building artificial neuron network (ANN) model for predicting values but facing problem:
Input:
...
- 13
0
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1
answer
395
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Sports prediction using Keras NN stuck at ~0.5 accuracy
I'm currently in the process of getting into data science, ML, and especially neural networks (coming from a "pure" software engineering background/degree). I did some models on classic ...
0
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2
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3k
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