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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1answer
30 views
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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2answers
54 views
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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1answer
15 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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1answer
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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12 views
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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1answer
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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8 views
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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1answer
18 views
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
61 views
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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49 views
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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17 views
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
28 views
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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13 views
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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13 views
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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1answer
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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19 views
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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8 views
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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0answers
10 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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47 views
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
29 views
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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0answers
42 views
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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0answers
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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6 views
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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22 views
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.
<...
