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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483 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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How to auto-moderate ads using machine learning? [closed]

There are ads, they consist of a title + description + pictures and some other features. Text is in Russian or Romanian language. There are 3 tasks: to determine whether the category is correct ...
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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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852 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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69 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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1answer
263 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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658 views

'range' object cannot be interpreted as an integer for Univariate Timeseries prediction [closed]

I'm following this link for time-series forecasting. While splitting the data set to create the data for the uni-variate model this Panda's TypeError occurs. ...
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20 views

How can I create a model to predict X,Y,Z coordinates? [closed]

Let's say I have a dataset of fish and this data set has X,Y,Z coordinates over a course of time along with other properties of the water and the name of the species. For example, ...
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Ideal framing of data from LSTM + adding static features

I'm dealing with a problem that I'll try to simplify here : You have a land where you can plant seeds and water them. On each day, you have the total area being watered and you have area that has just ...
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32 views

Drowsiness Detection issue understanding LSTM input shape

I’ve difficulty in understanding LSTM input shape. For example. I’ve 2 videos out of these 1 is categorized as Awake (0) and 1 as Drowsy (1). I preprocessed them to extract Eye Aspect Ratio and Mouth ...
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Difference between cell state and hidden state

What confuses me the most about LSTM cells are the cell state and hidden state. How are these both different from each other? What information do they both carry?
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How to interpret this Plot of Model Loss from a BiLSTM model?

Hi everyone, the above graph is produced by a BiLSTM model i just trained and tested. I can't seem to interpret it while it is very different from the references that i acquired by googling online. ...
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ValueError : All input arrays (x) should have the same number of samples in LSTM [closed]

I have the following network where I want to use two different time windows for my lstm network, but got this error. Could you help me to solve that? ...
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Is window based sequencing a good idea to obtain more training data for LSTMs?

I am trying to do an unsupervised autoencoder based outlier detection for time series using LSTMs. Here, there are multiple time series, and an entire series is to be considered as an outlier. However,...
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1answer
256 views

Calculation of Output in LSTM Many-to-One Architecture

I'm new to Recurrent Neural Network but I want to train my data with LSTM but I'm having a trouble to understand LSTM Many-to-One architecture. Suppose the size of my data is ...
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Does the Context Vector consist of hidden state and Cell State or just the hidden state?

LSTM's carry a hidden state and a cell state with them. Now, in a standard encoder-decoder model, we pass the Context Vector from the encoder to the decoder. Does, this Context Vector consist of just ...
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Forecasting Multiple (few hundreds) uni-variate time series with inflated zeros

Hello Practitioners, Being a newbie seeking help to gain experience in Data Science. Lets take a scenario where a big company wants to forecast its sales (a specific product) across different stores ...
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1answer
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Does the output of the Sequence-to-Sequence encoder model exist in the same semantic space as the inputs (Word2vec)? [closed]

Does the output generated from the LSTM encoder module exist in the same semantic space as the original word vectors? If so, say for example we have a sentence and we pass it through the encoder to ...
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multivariate LSTM for varying sequence length and varying Batch size

I receive data from a sensor and after some preprocessing, I get data points (1-18) with 8 features in every for-loop. That is, in one for-loop I get data of size 10x8 points while in the 2nd run, I ...
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2answers
844 views

Multivariate LSTM RMSE value is getting very high

I want to predict a time series with multiple variables. I am using Keras's LSTM class. Here is my data set description : I want to predict var1(t-1) and my X variables are var3(t-1) , var4(t-1) , ...
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1answer
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Looking for an advice based on an output of a LSTM model

I have fitted a LSTM model first using keras. Data:I have a time series with 560 observations. From that I trained the model using first 500 observations and then evaluated the model using last 60 ...
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Implementation of the LSTM using Keras in R with multiple outputs

I'm implementing the LSTM based on this tutorial (https://blogs.rstudio.com/ai/posts/2017-12-20-time-series-forecasting-with-recurrent-neural-networks/), but the example consider multiple inputs with ...
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640 views

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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24 views

Algorithm for Multivariable timeseries prediction (COVID forecast)

I am trying to forecast tomorrow's COVID-19 cases in my country. I tried a simple Linear Regression implementation based on the "new_positives" field but it does not work very well. I had ...
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1answer
64 views

Recommender Model for Human Action in Income Protection

Problem Domain I'm working on a project that involves building a model to provide recommendations on the next best step for Human supervisors to take on income protection claims. Income protection is ...
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1answer
522 views

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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1answer
739 views

Predicting parallel time series with multiple features

I am trying to predict sales for 2 departmental stores which share similar demographic properties. My goal is to make a single LSTM model to predict sales from these parallel time series having ...
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1answer
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Using pretrained LSTM and Bert Models in CPU Only Environment - How to speed up Predictions?

I have trained two text classification models using GPU on Azure. The models are the following Bert (ktrain) Lstm Word2Vec (tensorflow) Exaples of the code can be found here: nlp I saved the models ...
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1answer
592 views

Metrics for presenting RNN/LSTM result

I am working on a two different architecture based on LSTM model to predict the users next action based on the previous actions. I am wondering, what is the best way to present the result? Is it okay ...
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3answers
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extraction information from resume

I have a project in machine learning in which I need to analyze a curriculum vitae. for that I have to write a python program. It uses basic techniques of Natural Language Processing like word ...
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Can I use LSTM models to evaluate multiple, independent time series?

Let's say that I would like to predict the temperature tomorrow. I could use the approach whereby I train a model based on a time-series dataset collected from a single location (for example, see this ...
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How is the input gate in the LSTM learn?

How is the input gate neural network trained what to remember by propagating the error rate from predicting the next word in the language model? How does it help it to learn if it remembered the right ...
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Continue with LSTM or try other approaches?

I am trying to predict error (deviation from the actual behavior) in a signal, here is an example Blue -> Reference/Actual signal (cannot be fed to the network, used to calculate error only) Orange ...
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What information does Hidden State and Cell State carry? [duplicate]

What information does Hidden State and Cell State carry? Do they carry the summary of the input sequence or what?
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1answer
238 views

How to split a dataset into train and test sets for time series (multiple step-multiple output forecasting)?

I am trying to use an LSTM neural net to do multiple step / multiple output forecasting (I predict multiple values in one time knowing some values in the past). But, I have realized that I must be ...
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1answer
30 views

what is the complexity of a bidirectional recurrent neural network?

In particular, what is the complexity of a bi-directional recurrent neural network taking into account the variants of LSTM and GRU as well for training? I am hoping if I can get links to some ...
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1answer
23 views

Output vector size of a LSTM

Is the size of the output vector of all machine learning algorithms the same? Can't an ML algorithm predict only one value as output? I have trained an LSTM network with X, Y, heading, speed(from ...
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LSTM predicting same word repeatedly

I am sure that this has happened to you if you have trained an LSTM model. The LSTM model predicts the same word 2 or 3 times. Now, I am not saying that for every input it has the same output. I am ...
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1answer
191 views

[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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Is Keras LSTM the right choice?

My Keras LSTM NN improves to a val_loss of around 0.005 when training with 75% of my 4000-s long time series. I've ran the GridSearchCV to tune the hyperparameters ...
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1answer
42 views

LSTM Target Is Also One of It's Inputs?

I have two input arrays that include both historical and forecasted data, and one input array that is only historical. I'm trying to predict (or "forecast") the latter array given the ...
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LSTM model performs worse after retrains

I'm using a bidirectional, stateless LSTM (Keras/Tensorflow) for time series prediction.The procedure is as follows: We have a singal: $[0, 1, 2, 3, 4, \ldots, n]$ We scale values: $x_i ^ {scaled} = ...
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1answer
26 views

How to give a 3D Tensor as input to LSTM

I'm having X_train of shape (1400, 64, 35) and y_train of shape (1400,). I want to give X_train as input to LSTM layer and also ...
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How is the Gaussian noise given to this BLSTM based GAN?

In a conditional GAN, we give a random noise along with a label to the generator as input. In this paper, I don't understand why in one section of the paper, they say they are giving the random noise ...
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1answer
1k 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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1answer
11 views

Preparing multiple training time-series for Keras LSTM regression model training

I have training data organised in a numpy array in which: * column is feature - last one is the target, * every row is one observation. The thing is that this 2D ...
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9 views

How to fit the LSTM model correctly with series data

I have a small data set with the transformed series vector data with the music genre. The goal for me is to use the LSTM model to learn the non-linear pattern each row for genre classification. The ...
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1answer
100 views

Impact of varying sequence length in ensemble GRU model

I am using ensemble gru for my project and keeping different cell sizes for different models !For example, first gru model is of size 16 and the second is of 8 and 4 for the third model. The model is ...

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