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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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About applying time series forecasting to problems better suited for reinforcement learning, like toy example “Jack's car rental”

"Jack's car rental" is an example of a reinforcement learning problem, proposed in the Sutton & Barto book, in which the goal is to optimize the daily distribution of cars in two locations of the ...
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predict future value in every one hour using (t+60 minutes) LSTM neural network in python

I have a data csv file including with three inputs and two output with time series. Here data took an every one hour one hour. So I need to predict my next future value at t+60 according to the ...
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Job Recommendation System

I am building a Job Recommendation System where I have Student Data for different subjects in Machine Learning(Data Viz, Python, Statistics, etc) and their skills from the resume. Need to Recommend ...
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Which neural network to choose for classification from text/speech?

I am considering two tasks: Dialog Act Classification from Text (e.g. classify to: question; opinion; ...) Emotion Recognition from Speech (e.g. happy; calm; sad; ...) Which DL model should perform ...
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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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15 views

Using LSTM's on Multivariate Input AND Multivariate Output

I have a very small dataset, only about 40 rows, that has historical usage data for a few categories (roughly 20). I strongly suspect that these categories are dependent in a partial-zero-sum-game ...
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1answer
9 views

LSTM for prediction of next location step - help with standardization

I have a few questions regarding the topic and I hope someone might have experience with any of them. What I am trying to do is train an LSTM network, whose input is a sequence of N steps in a XYZ ...
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5 views

LSTM Autoencoder on Patterns of Labels

Currently, I am trying to do anomaly detection on univariate data consisting of labels. For example: [A, A, B, C] is good but [A, A, A, A] is anomalous. I'm dealing with more than just ABC. Is an LSTM ...
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RNN and LSTM to remeber short term text data [closed]

Does RNN with LSTM can remember text data , about four to five lines?
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32 views

Keras/TF: Making sure image training data shape is accurate for Time Distributed CNN+LSTM

The comprehensible data shape to me is like: (9186, 120, 120, 1) this means 9186 entry, of 120 by 120 pixel grey images. I learnt that using Time Distributed to design a CNN combined with an LSTM ...
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10 views

How to train single LSTM model on multiple independent data?

I have to do time ahead prediction of memory and cpu utilization of different hosts in my IT infrastructure. For example, consider host1 having 2 columns of data for cpu and memery utilization for ...
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image caption generator

I see two models of image caption generator online: In the above model, the first LSTM cell of decoder takes the entire image as an input. In the above model, all the LSTM cells of the decoder take ...
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1answer
27 views

GRU/LSTM models - Train/Test split

I drove myself into a corner with this, can someone please explain? I feel I'm missing something obvious... If, for LSTM, each layer is trained with inputs from t and t-1, than that'd mean that if I'...
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Difference in labelling and normalizing train/test data

I am working on a dataset comprised of almost 17000 data points. Since it's a financial dataset and the components are many different companies, I need necessarily to split it by date. Therefore, ...
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2answers
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Are RNN or LSTM appropriate Neural Networks approaches for multivariate time-series regression?

Dear Data Science community, For a small project, I've started working on Neural networks as a regression tool, but I am still confused about possibilities of some variants. Here's what I am aiming ...
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23 views

Best Architecture for LSTM Network for Stock Prediction

I am building an LSTM model to predict stock prices using TensorFlow. Is it best to structure the model so that it accepts $X=[x_0, x_1, ... x_{n-1}]$ and predicts $y=x_n$, or accepts $X=[x_0, x_1, ......
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Modeling keras LSTM sequential vs functional api

I'm trying to compare 2 simple lstm's build with keras, one is of the Sequential api and the other is from the Functional api. Both models are getting sequences of 5 - each sequence has 5 features (e....
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How to apply classification algorithms for timetable rescheduler?

I have the following dataset: Name of assignee:Alex Time to start work on task: 10:00 17-01-2019 Time to finish work on task: 12:00 17-01-2019 Assessment results: A Type: Article URL: http://... ...
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1answer
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How to pass 2 features to LSTM , one of them is one-hot-encoded with Keras?

I have a very simple LSTM model ...
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11 views

Embedding when using an RNN and zero-padding on input strings

I have started developing an RNN/LSTM in tensorflow to take in short sentences (typically of length 5-15 tokens) along with a second categorical variable. The goal is to create an encoder-decoder to ...
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Python LSTM Back propagation doesn't pass gradient check

I am trying to code a Recurrent neural network in python and I am having trouble getting the back propagation step to correctly calculate the gradients as when I check it using gradient checking the ...
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1answer
65 views

Multivariate time series forecasting with LSTM

I have the following problem: $\mathbf{Y}(t)$ = real valued random vector of observations at time t, $Y_i(t) \in R_{(0, 1)}$ $\mathbf{X}(t)$ = real valued random vector of observations at time t, $...
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Slightly changed keras LSTM architecture for train and test

I'm trying to build a keras LSTM model that is similar to a language model (something like predicting next word , after seeing a few previous words). My data has 2 features - a previous score and a ...
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15 views

Which loss function to use for predicting traffic vehicle count?

I want to predict the traffic vehicle count of different junctions in a city. Right now, I am modelling this problem as a regression problem. So, I am scaling the traffic volume (i.e count of vehicles)...
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30 views

Scaling values for LSTM

I have the following time series data set Each row is a unique Item, and each column shows the amount purchased per day. There are a total of 33 columns. I'm taking the first 32 columns(leaving out ...
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Training a LSTM on two merged writing styles (say Shakespeare and Frost)

I was trying to develop intuitions on how two writing styles can be merged (if at all they can be merged) into a single LSTM and then get meaningful results from the same. Can anybody provide me ...
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Predicting if an Aribnb listing will be sold out on certain dates

The use case: A user is searching for a listing on Airbnb with specific dates. I need to predict the probability that the listing will be sold out soon. Also, if possible, when it would be sold out (...
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1answer
25 views

Connect a dense layer to a LSTM architecture

I am trying to implement an LSTM structure in plain numpy for didactic reason. I clearly understand how to input the data, but not how to output. Suppose I give as inputs a tensor of dimension (n, b, ...
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2answers
76 views

LSTM vs ARIMA for demand prediction

I'm new to the field of time series prediction. I'm looking for a demand prediction model to predict when the product will be sold out from the online supermarket (when the supply is known in advance)...
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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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Using the Python Keras multi_gpu_model with LSTM / GRU to predict Timeseries data

I'm having an issue with python keras LSTM / GRU layers with multi_gpu_model for machine learning. When I use a single GPU, the predictions work correctly ...
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2answers
42 views

Validation loss is not decreasing

I am trying to train a LSTM model. Here is train and validation loss graph. Is this model suffering from overfitting problem ?
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1answer
44 views

Recurrent Neural Network (LSTM) not converging during optimization

I am trying to train a RNN with text from wikipedia but I having having trouble getting the RNN to converge. I have tried increasing the batch size but it doesn't seem to be helping. All data is one ...
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2answers
61 views

Understanding LSTM input shape for keras

I am learning about the LSTM network. The input needs to be 3D. So I have a CSV file which has 9999 data with one feature only. So it is only one file. So usually it is ...
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2answers
115 views

training neural network

I was given the task as follows, Scrape articles appearing in Times of India since 2010 on HIV and AIDS. Classify them using training a neural network of your choice. Find patterns in those ...
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32 views

Triplet loss training problem

My results are very poor and I cannot make out the reason on why is it so? I am using euclidean distance measure for hard mining of triplets. It is prior to training with the initial random set of ...
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1answer
24 views

Information about LTSM RNN backpropagation algorithm

I am attempting to make a LTSM RNN in python from scratch and I have completed the code for forward pass but I am struggling to find a clear outline of the equations I need to calculate to get the ...
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28 views

time-series forecast with lstm and known future features

I am working on a lstm project. I want to use the model to predict a time-series and I am using a rolling window approach. I want to predict electricity consumption for industrial plants on a daily ...
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1answer
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Need to make an multivariate RNN, confused about input shape?

So I've seen this: Keras LSTM with 1D time series And this: Multi-dimentional and multivariate Time-Series forecast (RNN/LSTM) Keras But I still don't quite get it. I have many, many, many accountIDs,...
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28 views

Understanding how to use ConvLSTM for multistep ahead forecasting

I have a problem where I have transaction data for many banking accounts. The task is to train a model on historical debit/expense transactions and then forecast expense transactions for the next n ...
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1answer
60 views

Can LSTM Predict The Next Few Days Of Stock Price?

I have searched many websites and forums describing stock price forecast using LSTM. They shared two things in common: one is that all the sources make predictions with same set of data and none of ...
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Recommended model for univariate or multivariate multistep ahead time series forecasting

I have a dataset consisting of recurring and non-recurring expense transactions from bank accounts, as well as other features describing the bank account and each transation. I aggregate these ...
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23 views

inverse transform test data with LSTM shape problem

I'm trying to use a LSTM with two feature but when i make predictions are can inverse transform them back as i seem to have a dimension problem. ""cannot broadcast shape (761,10),(2),(761,10). Im ...
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23 views

Need Help with inverse transform test data with LSTM

I'm trying to use a LSTM with two feature but when i make predictions are can inverse transform them back as i seem to have a dimension problem. ""cannot broadcast shape (761,10),(2),(761,10). Im ...
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1answer
65 views

Machine learning Classification model for binary input and output data

I have a large longitudinal dataset with 5 minutes granularity for a period of around 30 months from thousands of households. I want to classify them as binary output (0/1) based on the input which is ...
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1answer
31 views

What is the advantage of using RNN with fixed timestep length over Neural Network?

More often than not, I see RNNs being used with fixed length timesteps. So what is the difference between the following two networks? RNN with timestep length of 3 over sequence Xt. NN with inputs x(...
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1answer
20 views

Defining Input Shape for Time Series using LSTM in Keras

I have been trying to model Time Series forecast using Keras LSTM algorithm. My dataset consists of weekly sales data from Jan-2016 and I also have external features such as Festivals/Events each ...
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13 views

LSTM model for multiple sequence data

I have 38 data set and each set contains the different length of sequences(Each of the set contains A-G in different number). This data is from different student to perform a task. So each sequence ...
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keras multi input LSTM , performing worse than a random forest model ran on one of the inputs given to keras

I have a multi-input keras LSTM model, which takes a tweet input which is converted to word vectors, padded and provided as an embedding. The second input is about 22 fields of numeric data. I ran a ...
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What is the correct format of the test input for LSTM neural network? [closed]

I have learned some tutorials for LSTM time series prediction. According to that tutorials, My training data format would be like, NOTE : This data is only for example. this is not the real data. <...