Questions tagged [keras]
Open source high-level neural network library for Python and R. Is capable of using TensorFlow or Theano as backend.
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why does epoch sometimes not stop at the set patience?
I'm confused as to how 'patience' works on keras. as far as I know, if we set patience=10 then if in the last 10 epoch the loss doesn't decrease significantly or even continues to increase, then the ...
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Is it ok to have low validation loss from the first epoch?
I'm trying to implement Neural Collaborative Filtering recommender system using Keras, the dataset I'm using is movielens-small. Whatever I do to hyperparameters or network, when training, the ...
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Binary input variables for a Keras Neural Network
I have a set of forty predictors each of which are binary. I’m using elastic net logistic regression in addition to a random forest
Is there any reason why you could not use binary inputs for a Keras ...
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Why are my deep learning models giving unreasonably high accuracy on test data?
I'm trying to do sarcasm detection on Twitter data to replicate the results mentioned in this paper. Binary classification problem. For that I used a separate set of unlabeled tweets to create the ...
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Managing Missing Values in LSTM Time-Series Model using Keras Masking Layer
I am currently working on developing an LSTM model using six time-series data as an input with the objective to predict one of them. However, the data contains missing values that need to be addressed....
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RNN/LSTM networks on spectrograms underfitting massively - is the CNN encoder a prerequisite?
I am prototyping a pipeline on the FSDD dataset (audio/10-class classification); the audio data are loaded with librosa, 0-padded/trimmed to 0.5 sec (4000-dimensioned numpy vectors) each and converted ...
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How to calculate the decay rate given an initial learning rate and final learning rate for schedulers when training neural networks?
I am training a neural network in TensorFlow and I would like to use firstly an exponential decay optimizer scheduler (https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/schedules/...
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Handling Molecular Graphs and Numeric Data in Parallel
I haven't been able to find much material on it so I am not sure if I'm couching my problem in the right words. I'm using deepchem with keras and rdkit. Essentially I have some molecular data and I ...
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Running SVM on positional embeddings using keras for text classification
How can I run SVM on a large text classification dataset for detecting fake news of 400 thousand entries that uses positional encoding for embeddings from keras and has a maximum sentence length of 15 ...
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Prediction model for [parameter vector] to [time series]
Say I have a function $F$ that takes in a parameter vector $P$ (say, a 5-element vector), and produces a (numerical) time series $Y[t]$ of length $T$ (eg $T$=100, so $t=1,...,100$). The function could ...
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F1 score for validation and testing datasets is different
I have the following F1 score function that I use for the model when I train it as part of metrics and as well during prediction:
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Much better results when standardizing features to train LSTMs
I have a data set of time series. Each time series represents trajectories of the same path taken. So, the time series captures acceleration in $x$, $y$ and $z$ direction, respectively for the ...
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How to generate new data with a VAE?
I have built the following function which takes as input some data and runs a VAE on them:
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Single input - multiple outputs with different loss functions in Keras: how is the gradient computed?
I've implemented a neural network with single input - multiple outputs using Keras API. The general structure of the network is like in this figure:
Because each branch does a different task, I ...
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Recurrent dropout in keras: is the Semeniuta method equivalent to the Gal and Ghahramani method from the point of view of variational inference?
as the title. from this post https://stackoverflow.com/questions/44924690/keras-the-difference-between-lstm-dropout-and-lstm-recurrent-dropout I have recently learned that the implementation of ...
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Grid search with KFold CV and Early Stopping - which validation set?
I'm training a NN to solve a regression task.
I want to perform a grid search with Kfold combined with early stopping, but the only way I found is by passing a new validation set (different from the ...
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How to determine if two images contain the same object without a dataset?
The problem I am trying to solve is, given two images, determining whether they contain the same object or not. Here is an example:
The first two images contain the same object, while the third image ...
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Predict angle by linear loss
I'm trying to solve following nonlinear regression task: We got fixed point from which the bullet is released with some start speed v0 (value v0 changes each time). On the opposite side we generate ...
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Scikit-learn and Keras' MLP very different with same hyperparameters
I'm using Multilayer Perceptron ANNs at the very beginning of my project (it's a binary classification problem). Because it's simpler, I started with Scikit-learn. I got a magic result, with my model ...
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Why does a neural network trained with random data and fixed initialization have different weights between runs?
I wrote a simple code that creates a neural network with two dense layers and then trains it. In this code, the initial coefficients of each layer are fixed. Why do the answers change every time? (In ...
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Why am I obtaining values close to zero when using a NN for regression? [duplicate]
Here is the dataset.
I tried converting this implementation into its analog with Keras. Why are my predictions SO bad? They are almost always close to a single number. Doesn't matter if I use more ...
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Imbalanced binary classification results discussion
Hello I'm wondering how do you consider these result For binary classification with class imbalance.(84% to 16).
Accuracy 96 Precision 94 Recall 80 F1 86 Roc_auc 98
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Return_state in LSTM Keras
Using Return_state = True, we return the last hidden state twice and the last cell state. My question is why the last hidden state is returned twice. Why is that needed and in which application?
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Multilabel Classification: Accuracy is very low. Metric or Model, which is inadequate?
In my multilabel classifaction problem, which I approach similarly to what can be see in this post: How does Keras handle multilabel classification?, the resulting accuracy only increases from 2% to 5%...
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Keras Prediction one step beyond
I am trying to make time series forecasting with keras. Has any one observe the phenomenon where the model can predict the next value after the current (the one that should predict)?
If in fact I move ...
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Loss Function for Binary Classification with Multiple Correct Choices
I have a binary classification problem, where there are multiple correct predictions, however, I would consider the prediction to be correct if the highest confidence prediction of a 1 is correct.
I ...
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Is it possible to do feature selection within the Keras deep learning framework? [closed]
I know most people perform feature selection running RFE on a linear regression model, for example, BEFORE training the model with Keras.
However is it possible to do it within the training procedure ...
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What are the differences between AdaDelta and RMS prop in Keras (if any)? [duplicate]
I have read many references which suggest that RMSprop and Adadelta are basically same, just developed independently. However, Keras has two different classes for it. Also, it allows RMS prop to have ...
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how to determine epochs value, momentum and learning rate? [duplicate]
I have dataset with 70k-90k rows 42 columns and one of them is my target variable with 3 class label (yes, no , not applied). I'm applying sequential model (MLP) to my data, I just used random values ...
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Understanding keras layer structure/notation
I am trying to understand the following keras model:
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Recommender System: How to predict user ratings using Linear Regression and User/Item Embeddings?
I hope this is the right forum for this, but here goes:
I am currently doing a capstone project for a course. Part of that is building a recommender system using various algorithms such as NMF, kNN, ...
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Predicting multiple items with different customer behavior using neural network
I'm working on neural network model to predict the number of products to order during promotion period.
My question is that, if I have multiple items with different user behavior e.g.
fresh milk (...
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How can reduce improve my ANN accuracy and reduce overfitting?
My ANN model produces classic overfitting characteristics, producing high R2 values (90-99%) but low accuracy scores (10-40%). I'm currently inputting 28655 data entries, using 8 input features to ...
reubenturner
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Learning stochastic pattern using RNN
I have a pattern of count time series of vehicle demand as shown below.The time series is generated as follows:
Categorical Random Variable, x = {0,1,2} and p(x) = {0.6,0.3,0.1}
low vehicles = 1 + x , ...
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High validation accuracy and training accuracy but low test accuracy
I have a LSTM model that has good training accuracy(~90%) and excellent validation accuracy(> 95%) but it gives poor results when I test it on data it hasn't seen. I am training hyperparameters ...
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Best hyperparameter is not consistent among different seeds
I do hyper-parameter tuning on my network and it outperforms the simple classifier. The difference in classification is considerable after hyper-parameter tuning. But, the problem is that an optimal ...
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Using "X_test, y_test" as validation data on Keras
I was looking at some examples on how to use Keras for Regression and I came acrossed some tutorials that used X_test and y_test as validation data and then use them again at .predict.
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Sequential Binary Imbalanced data classification with LSTM
I'm building an LSTM sequential Binary Classification Model, the data is highly imbalanced like say Fraud detection case.
After building an LSTM model on Sequential Vectorised data, I'm getting a very ...
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Validation performance is really problematic; should I give up on increasing the validation performance of my deep learning model? [duplicate]
I am working on a multiclassification problem using time series data. Three datasets are utilized in this study. My deep neural network performs satisfactorily across two different data sets. However, ...
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In what terms, training steps of my DG-GAN differs from the one of others?
Why does Deep Convolutional Neural Network GAN, trained using my step sequence, doesn't performs well as in the GFG DC-GAN Tutorial example? Even tho my code is similar in logic and resembles same to ...
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Neural network loss not dropping to expected levels
I am attempting to create a neural network that can learn to evaluate chess positions. I'm following along with this paper and trying to recreate its results. The general idea is to have the NN ...
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Proper masking in MultiHeadAttention layer in Keras
I am new to Transformers and I am trying to create a very simple model (not NLP area) for processing data of variable length (not sequence data because for my problem order in data does not matter). ...
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To understand the underlying math of GRU neural network in TensorFlow Keras
I tried out a simple GRU network with only 1 layer, 1 input tensor and 1 output, to verify its actual network connection (input nodes->hidden layer->output) by doing the manual calculation with ...
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Training loss after last epoch differs from training loss (same data!) during evaluation
I am building a deep convolutional model with a custom loss function. As a first step, I am trying to bring training loss down as far as possible to see if my model can overfit.
Training with on only ...
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Need Help for reward function in reinforcement learning
I've created a RL to trade on an artificial custom financial asset(Complete Code). This is my Dataframe(enviroment) made of 'Close' price and 'Volume':
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Interconnections between embeddings layer and LSTM layer
I'm trying to build a text classifier with keras using word embeddings (glove) and a RNN (in this case a LSTM) using keras. I searched in several sites and decided to start with this configuration:
<...
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amount of parameters of Conv1D vs Conv2D (Keras library) [duplicate]
imo, I should have the same amount of parameters if I construct Conv1D and Conv2D whereby in Conv2D one dimension is set to 1 (as if it was eliminated)
here are snippets from the summary function of ...
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validation accuracy spikes on Unet Neural network
I'm a computer science student actually working on my graduation thesys based on a Unet ANN.I'm using Kolektor Surface-Defect Dataset 2 (i'll leave the link below) that is a dataset of annotated ...
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is it good to have 100% accuracy on validation?
i'm still new in machine learning. currently i'm creating an anomaly detection for flight data. it is a multivariate time series data that include timestamp, latitude, longitude, velocity and altitude ...
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Correct loss function and metric for regression of count data in neural network
I am using a convolutional neural network to predict the number of occurrences of a certain pattern in time series data. Since there might be potentially any count of such patterns in a time series, I ...
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