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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Generate new sentences based on keywords

For example, for a domain specific neural network in Fashion, with the Keywords light, dress, orange, cotton. It could output: This gorgeous orange summer dress is great for wearing on sunny camping ...
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1answer
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Proper way to make Train/test split on Time-Series

I want to create a model with LSTM to predict a user the next purchase value. For this I have used I used a user's purchase history. I have created the model and it works well, but honestly, I don't ...
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Why does the forecasting of this LSTM model look like a steady line?

This is a multivariate multistep problem using LSTM NN model. I am trying to forecast one variable by means of the other variables. However, the forecasting output looks like a horizontal line. Kindly ...
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LSTM Timeseries recursive prediction converge to same value

I'm working on Timeseries sequence prediction using LSTM. My goal is to use window of 25 past values in order to generate a prediction for the next 25 values. I'm doing that recursively: I use 25 ...
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Predicting sequence element based on the previous M and the following N elements

I have an array of sequences of equal length, each sequence contains 300 numbers (M=300). Each element in a sequence is a number from 1 to 9: ...
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Understanding Timestamps and Batchsize of Keras LSTM considering Hiddenstates and TBPTT

What I'm trying to do What I am trying to do is predicting the next data-point $x_t$ for each point in the timeseries $[x_0, x_1, x_2,...,x_T]$ in the context of a date-stream in real-time, in theory ...
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1answer
190 views

Error on custom RNN/LSTM with multiple inputs

I want to implement a custom RNN/LSTM model similar to this. The model should take two separate vectors as input and process them. I was following keras tutorial to implement a custom keras layer and ...
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17 views

model has not yet been built

I'm making CNN-LSTM model for forecasting but I'm receiving this error : This model has not yet been built. Build the model first by calling build() or calling fit() with some data. Or specify ...
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1answer
617 views

Train LSTM model with multiple time series

I am predicting energy usage for a bedroom within a school residential building with date, temperature, and humidity as input features, using 7 time-steps and ...
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LSTM low training/validation error but really bad predictions

I'm building a LSTM model to create an automatic drums composer. I'm following this post: LSTM Metallica I've built my model and done all the enconding, I was able to emulate the behavior of the ...
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Problem in input shape Keras-LSTM

I want to make a predictor using Keras LSTM model. I have a sequence of places visited. The task is to predict the last destination. I went through different examples but it seems I am not able to ...
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How to draw a simple LSTM network

I'm new to deep learning, I am learning LSTM for my PhD work. This is a simple LSTM network for sequence classification. This code is from MATLAB tutorial: ...
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Time series binary classification [closed]

Which deep learning architecture and algorithms do you most recommend for time series classification problem? Of course LSTM, I am looking for state of the art papers.
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35 views

Understanding the concept vanishing gradient and exploding gradient problem in terms of training data

I'm trying to figure out the essence of the concepts "vanishing gradient and exploding gradient problem" in terms of real-world input-output training examples instead of in terms of the properties of ...
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How respective gating functions are ensured in LSTM?

I'm studying the Hochreiter-Schmidhuber long-short term memory recurrent architecture. The overall idea, information flow and manipulation is clear, and it seemingly works, but what I cannot ...
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1answer
20 views

Difference between stacked lstm vs attention mechanism in LSTM

What is the difference between stacked lstm vs attention mechanism in LSTM? It seem to me that both produce the same context vector at the end. EDIT: From suggestion by @shepan6, the difference in ...
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1answer
98 views

ValueError: Error when checking input: expected the_input to have 3 dimensions, but got array with shape (14174, 1)

hope you're all doing good ! I am working on Automatic Speech Recognition with Python with the LibriSpeech Dataset. After preprocessing the audios data and applying an "MFCC featurizing" I ...
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1answer
29 views

How to identify new clusters that the training data has never seen

I have to identify the different operational states of a server. I have readings related to the different sensors of the server ( like temp sensor,fan speed sensor,job load sensor etc).The data I have ...
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Generating new sequences from given set

I got two classes namely positive and negative with 1500 samples on each a total of 3k. A sample sequence is like: ...
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LSTM (Long Short-Term Memory) network usecase

I am new to LSTM and trying to put in a real life implementation, but not sure whether LSTM suits well. The use case is as following: There are many warehouses in different regions. Hourly, trucks ...
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Autoencoders for the compression of time series

I am trying to use autoencoder (simple, convolutional, LSTM) to compress time series. Here are the models I tried. Simple autoencoder: ...
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1answer
2k views

Multi-Step Forecast for Multivariate Time Series (LSTM) Keras

I have been trying to understand how to build LSTM model for multivariate time series forecast using Keras but I am still unsure how to present the data in the correct shape. ...
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1answer
837 views

Is it always better to using stacked LSTM than single LSTM?

I am currently studying LSTM and RNNs. I came across several concepts like Multidimensional LSTM and Stacked LSTM. I have used Stacked LSTM and it gives me a better performance than single LSTM. As ...
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how to build lstm with functinal api?

I am having a time series prediction problem and the data set has 4 variables. My data set is like below: ...
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1answer
48 views

What is the output of multivariate LSTM model?

I am currently trying to build an LSTM model by using multivariate inputs, but I don't understand what exact output I am predicting. I am currently using 5 features in the data i.e. 'Time', 'Avg CPU ...
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1answer
72 views

pandas TypeError: 'range' object cannot be interpreted as an integer

I'm following this link for time-series forecasting. While splitting data set to create the data for the uni-variate model this ...
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1answer
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Prediction Outputs from LSTM NN

I'm working with an LSTM network to predict the surface roughness due to biogrowth on ships. I've got a Network that fits the input data I have relatively well, the problem is when I'm using it to ...
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1answer
273 views

How can I tune LSTM hyperparameters?

If anyone is there to answer these, that'll be great. I'm in the midst of a Final Year Project on LSTM. Currently, I’m stuck and confused over LSTM codes. There are 4 hyperparameters that I can play ...
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26 views

Time series forecast for everyday for till a distant future

I have time series data for every single day from last 5 years with seasonal variation and a general increase in trend. This is what my data looks like: And I am trying to predict for every single ...
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2answers
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How can I build a self-attention model with tf.keras.layers.Attention?

I have completed an easy many-to-one LSTM model as following. ...
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1answer
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Using LSTM to predict next word performs poorly

I am training a model to predict the next word in a sequence, my data is comprised of Reddit post titles and is structured as: ...
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1answer
149 views

How to add previous predictions for new predictions in LSTM?

I am trying to train a model on a big data sequence like this [0.2 0.1 0.1 ..... 0.4 0.8] . I create X vectors with length 60 for inputs and Y scaler numbers as ...
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1answer
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LSTM's for timeseries with additional regressors

I have a dataset consisting of the weekly sales of 3,000 stores over the past 5 years, and have constructed a LSTM to forecast the next year of sales, given the previous year of sales. At each ...
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1answer
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Predicting next element of a sequence given small amount of data

I have data of bank branches and amount of revenue they have generated in a month. The data looks like this: I am tasked to find the expected revenue for the branch for the next month using machine ...
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1answer
685 views

Running out of memory when training Keras LSTM model for binary classification on image sequences

I'm trying to come up with a Keras model based on LSTM layers that would do binary classification on image sequences. The input data has the following shape: ...
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1answer
59 views

What does the below phrase in the lstm blog mean? - Data Science

I am a newbie to data science. I was reading this blog When I was half way through, I came into this sentence Further, each series of data has been partitioned into overlapping windows of 2.56 ...
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6answers
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When to use GRU over LSTM?

The key difference between a GRU and an LSTM is that a GRU has two gates (reset and update gates) whereas an LSTM has three gates (namely input, output and forget gates). Why do we make use of GRU ...
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1answer
103 views

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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1answer
219 views

What are the equations involved in calculation of the parameters of embedding layer?

I'm trying to perform sentiment analysis on some data using keras.I'm using embedding layer and then LSTM. I know that embedding layer decreases the sparsity of the one hot encodings of the words and ...
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3answers
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Why are predictions from my LSTM Neural Network lagging behind true values?

I am running an LSTM neural network in R using the keras package, in an attempt to do time series prediction of Bitcoin. The issue I'm running into is that while my predicted values seem to be ...
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1answer
169 views

The loss and accuracy of this LSTM both drop to nearly 0 at the same epoch

I'm trying to train an LSTM to predict the the Nth token using the N-1 tokens preceding it For each One-Hot encoded token, I ...
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1answer
31 views

LSTM-Model - Validation Accuracy is not changing

I am working on classification problem, My input data is labels and output expected data is labels I have made X, Y pairs by shifting the X and Y is changed to the categorical value ...
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1answer
24 views

How similar is Adam optimization and Gradient clipping?

According to the Adam optimization update rule: $$m \leftarrow \beta_1 m + (1 - \beta_1)\nabla J(\theta)$$ $$v \leftarrow \beta_2 v + (1 - \beta_2)(\nabla J(\theta) \odot \nabla J(\theta))$$ $$\theta \...
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Streaming sequence detection (Binary Classification) LSTM/GRU

I am currently trying to implement a model which can detect a specific sequence according to the training data which looks like the following: ...
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9 views

LSTM Neural Network gets stuck in a specific state when trying to predict new states over many time periods

I have built an LSTM neural network for category, or latent state, prediction. The data is more or less of the form: x1 = continuos number from current record x2 = continuous number from current ...
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14 views

Concatenating Encoder hidden states in LSTM pytorch

I am implementing a seq2seq autoencoder in pytorch: Q1) While it is true that we can keep the encoder as bidirectional, but can we keep the decoder as bidirectional as well(does it make any sense) if ...
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21 views

Multidimensional time series regression

I’m new to time series forecasting and I’m trying to implement regression models using both ARIMA and LSTM for a multidimensional and multivariate time series. The samples are indexed by time, ...
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122 views

How to provide future exogeneous data for lstm when predicting multiple steps

let say I have one timeseries, for which I want to predict $K$ future steps. Additionaly I have exogeneous information, for example dates of holidays, that have impact on my timeseries. Therefore my ...

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