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Questions tagged [lstm]

LSTM stands for Long Short-Term Memory. When we use this term most of the time we refer to a recurrent neural network or a block (part) of a bigger network.

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How smaller does the input data get reduced in a LSTM autoencoder

Question In a LSTM autoencder, how smaller does my input data(59 features) get reduced in a latent vector, which is usually located in the middle between an encoder and a decoder? Why did the ...
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How to predict value in every 120 minutes using LSTM in python

I want to predict value in every 120 minutes continuous using LSTM model. Here I wrote the code for predction. But I'm not getting proper prediction values . Here from start time I need to predict ...
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How to put data into a 1-dimensional ConvLSTM2D with keras?

I am attempting to adapt the frame prediction model from the keras examples to work with a set of 1-d sensors. I have android wearable sensor data and am designing an algorithm that can hopefully ...
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What does it mean when my test data accuracy is higher than my training data?

I'm using four years of data, training on the first 3 and testing on the fourth. Using LSTM w/ Keras. My test data set (which has no overlap at all with the training) is consistently performing better ...
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In Keras, how to get 3D input and 3D output for LSTM layers

In my original setting, I got X1 = (1200,40,1) y1 = (1200,10) Then, I work perfectly with my codes: ...
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Input of the decoder of a LSTM seq2seq neural network?

I have been trying to setup a seq2seq network with LSTM layers where the output of the network should be the seven day ahead forecast, given the previous fourteen days as input. I started with a ...
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2answers
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Why LSTM models do not require labels for each step?

For time related problems like, for example, stock prediction: Let's say we have 300 days of data, 10 features, and one target: the price. Why, for the training, we only need the price of the 300th ...
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15 views

very low val_acc in LSTM for predicting numbers in sequence

I have problem with my LSTM network or my data. I woudl like to create LSTM network to predict number based on previous N numbers. This numbers will be encoded piano notes. About my dataset: 1. I ...
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LSTM: how to use just context?

I would like to use a model with a bidirectional LSTM layer to predict a sequence of outputs from a sequence of inputs (of length $l$). To compute the output $o_i$ I would like to use the inputs $...
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LSTM prediction for many multivariate time series

Let's say we have 8,000 different time series where each of them has 10,000 samples and 25 features. The goal is to have an LSTM sequence to sequence model (using Keras) where one can use a sequence ...
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24 views

Generate sentences using given data [closed]

I am working on an automated insights generation use case where I want to generate meaningful sentences from given aggregated data. For example, Data: ...
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2answers
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Training LSTM with different sequence lengths in Keras functional api

I am trying to train an LSTM model using Keras functional API. My training data is of shape: >>> data.shape() (100000,variable_sequence_lengths,295) ...
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Buy/Trade strategy logic for Stock Market Prediction [closed]

I need help in formulating/ brainstorming a strategy for trading ie. logic for generating buy/sell/hold signals for my Stock Market Prediction Model. I am using Open, High, Low, Close, Volume indices ...
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Train LSTM RNN with multiple different sets of time series data in Keras

I am trying to set up a program where an airplane is taking off from one city and flying to another. Depending on a number of factors it can take different routes to get to the city. Since some ...
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1answer
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How to structure time series for binary classification in Keras?

I'm trying to classify churn (1 or 0) for a user based on day-to-day time series and activity levels, something like this: ...
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What will go wrong if we apply linear or other types of regression to translate sentences between two languages?

Disclaimer: I asked the question at https://stats.stackexchange.com/questions/408463/what-will-go-wrong-if-we-apply-linear-or-other-types-of-regression-to-translate, but didn't get any response, so I'...
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Long-term Recurrent Convolutional Networks (Keras) for Game Bot

I want to use CNN and LSTM to make a Game Bot. Basic idea is to capture 32 frames of gameplay, and then, for that sequence, predict an output. My gamebot is more like a self driving car. Capturing the ...
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Classify activity person go into and go out the car (behavior detection)

I'm working on the problem classify activity get out the car and get in. Also need to classify if upload and download activity going near the car Need advice how to fix problem of overfitting model ...
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Time Series Forecasting for Multiple Customers using one RNN

I have a product which has univariate and also multivariate time series data from multiple customers. I have variable amount of data available. Ranging between couple of years to couple of months. ...
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How to download BibTex raw dataset for deep learning (LSTM )?

I am trying to test my model on the benchmark text classification dataset "Bibtex". The Bibtex dataset is available in tf-idf vectors but LSTM works on sequences. Bag of Words is a vectorized ...
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How to arrange the dataset/images for CNN+LSTM

I am working on an image classification problem using Transfer Learning with Resnet50 as base model (in Keras) (For example Class A and Class B). There is a time factor involved in this ...
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1answer
22 views

Problems finding an LSTM model for classification

I am doing a study for the classification of musical genres using deep learning techniques. The work consists of making a classification using an LSTM model. I am using GTZAN as a data set, and ...
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1answer
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[Keras][LSTM] error due to shape mismatch

I have following data. Where I have 2 samples. Each sample I have 3 time steps each with 2 features. I intend to have 2 batches (to updates weights after every sample) ...
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24 views

Simple Keras LSTM for Time Series Classification

I've tried reading through a few tutorials but they all seem to involve more complex tasks that involve steps I don't quite understand and my not be necessary for my use, so I'm having trouble ...
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How do I implement masking in TensorFlow eager execution?

I am training a stateful RNN on variable length sequences (optional: see my previous question for more details). I padded the sequences to a fixed length with the value -1. The when batches are ...
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Using TF Dataset API to process sequences for stateful RNN

I am trying to use the TensorFlow (v1.13) Dataset API to save and load long sequences for a stateful RNN. Basically, lets say I have n_seq sequences, each fixed ...
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Predict future event using text and class

I have a dataset containing reports of events in a company when something occurred. The report have: Text description of the event Code classification of the event Date of the event The code ...
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23 views

Time series output of LSTM network has a much lower scale than the input scale

I'm trying to use an LSTM network to predict a sequence of a time series variable. I'm trying to predict a sequence of 3 elements based on the sequence of the previous 6 elements. The Keras code that ...
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19 views

What's the difference between hidden layer size and sequence length in RNN and LSTM?

I have been exploring RNNs in keras implementations. In the LSTM layer we have to provide a hidden layer size and also a sequence length. My question is, what does hidden layer size correspond to and ...
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28 views

What method will be appropriate for fitting this kind of data?

My data set has 15 independent variables and 2 predictors or response. The problem is to find a mapping between input and output variables. Basically, given a feature vector as input, the trained ...
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1answer
19 views

Smaller network width than output size?

I am trying to figure out if it makes sense that the width of the network could be smaller than the input/output size? So for example, I am giving the Neural Network 2048 numbers, and I am expecting ...
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Drawing Trees, finding Probabilities and Predicting

My first post here :) I have some transition states. Like below, where each row reflect to a specific process: ...
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1answer
44 views

Best way to classify plots which are overlapping?

I have an experiment in which it was done under two conditions. For each condition, the experiment was performed 26 times. The output of the experiment is a plot with 70 time indices. I would like to ...
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How to apply an RNN to forecast non-stationary time series?

Is it possible to predict a time series which is non-stationary, in the sense that, the dependent variable Y have an increasing trend? Therefore, the highest value of $Y$ in the training set may be ...
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How to get the right keras model.predict label (NLP problem)

I implemented a small LSTM neural network to predict the notes for a movie. But I have an interpretation problem to convert the prob_result that ...
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I am building a gesture recognition system using video data from ConGD Dataset and am not able to create the 5D array,as input to the network

I need a 5D input for my network using ConvLSTM and 3D-CNN. Converting the videos to an array of videos would contain a 5D array (Num of examples, Num of frames, FrameWidth, FrameHeight, NoOfChannels),...
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2answers
43 views

Loss value going down while accuracy remains constant?

While I am training, it seems like my loss is going down, but my accuracy remains constant throughout training. It always seems to go towards 0.0023 no matter how I tweak my network, input data length,...
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1answer
44 views

Using LSTM to predict binary classification - accuracy stuck at 50% - how to use statefulness

I am trying to use an LSTM model to make binary classifications; however when I train the model the loss stays around 0.69 (ie. -$\ln(0.5)$) and the accuracy at 0.5, which suggests to me the model is ...
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Hybrid Model : RNN + MLP + RNN

I am trying to develop a model, as follow: an RNN with three LSTM takes in the input (5|1|54), the 5 previous days and 54 feature. In the end of the first RNN I would like to take the mean and std of ...
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1answer
32 views

LSTM input and output for sentiment analysis

I'm studying this LSTM network: https://www.kaggle.com/paoloripamonti/twitter-sentiment-analysis ...
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1answer
73 views

How to design batches in a stateful RNN

I am using TF Eager to train a stateful RNN (GRU). I have several variable length time sequences about 1 minute long which I split into windows of length 1s. In TF Eager, like in Keras, if ...
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21 views

clarify convLSTM usage for regression

I am trying to use keras and convLSTM layer to predict future weather data based on previous weather radar pictures. I use i timesteps i.e. i radar images as input data. In my diagram, I assume i=3. ...
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60 views

LSTM Predict values out of test

I'm trying to predic stock values from a dataset, for example: Google stock. I have this easy model. ...
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27 views

Measuring uncertainty in an LSTM network using dropout in keras/tensorflow

I've created a simple LSTM network for testing ...
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0answers
14 views

ValueError: Dimensions must be equal, but are 256 and 12 for 'attention_layer/MatMul_1' (op: 'MatMul') with input shapes: [?,256], [12,256]

I'm working on a sequence-to-sequence approach using LSTM and a VAE with an attention mechanism. ...
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0answers
25 views

ValueError: Cannot convert a partially known TensorShape to a Tensor: (?, 256)

I'm working on a sequence to sequence approach using LSTM and a VAE with an attention mechanism. ...
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0answers
22 views

Duplicate QUORA question detection:Kaggle Dataset

I have tried to use 2 BILSTMs along with the attention layer but the validation accuracy is not improving at all. Could anyone suggest an alternative to increase the accuracy? Layer structuring: <...
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1answer
37 views

LSTM with target outside the timeseries

Say I want to predict the final size of a flower depending on the raining and temperature during 200 days. The flowers are in differents towns, so each flower has its own conditions of rain and ...