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Questions tagged [rnn]

A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed cycle.

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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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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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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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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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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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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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43 views

Architecture for linear regression with variable input where each input is n-sized one-hot encoded

I am relatively new to deep learning (got some experience with CNNs in PyTorch), and I am not sure how to tackle the following idea. I want to parse a sentence, e.g. I like trees., one-hot encoded the ...
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42 views

How to train the generator in a recurrent GAN (Keras)

I am trying to train a Recurrent GAN that is meant to generate geospatial movement data (sequences of 3-tuples of latitude, longitude and time). You may simply consider it a sequences of vectors with ...
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Build an Autocomplete model for document titles

I want to build an autocomplete model using RNN where input is article names (documents title). X: ['Billing', 'Loan status', 'Filling loan application', 'Contact Info', ...] The article name can ...
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33 views

Neural Network architecture

I'm interested is it okay to use RNN encoder-decoder model for my task. I have train data with session_id, movie_id and ...
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4 views

Sentence Embedding and mapping with the most likely sentence based on the inputted sentence

I have a text document and performed Sentence Embedding as Unsupervised learning in rnn. I want to map the most likely sentence in the document for the inputted Sentence.
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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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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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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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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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1answer
38 views

Sequential Modelling: Multiple Sequence to One or Sequence to Sequence

Suppose I have a single sequence of $x_1, x_2, ..., x_n$ and corresponding labels $y_1, y_2, ..., y_n$. An example would be a person makes website visits $x_i$ and the label $y_i$ tells us if there ...
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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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51 views

How to deal with unknown classes with a neural network classifier?

I have a small RNN with a softmax output, which succesfully classifies sequences within a known set of n classes. The model is only trained with known classes. Now I have the problem that there might ...
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65 views

Predicting next number in a sequence - data analysis

I am a machine learning newbie and I am working on a project where I'm given a sequence of integers all of which are in the range 0 to 70. My goal is to predict the next integer in the sequence given ...
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13 views

Separate scalers for input and output

For my problem I'm using python with Keras over Tensorflow. I'm trying to use LSTM to predict next event in events sequence. My dataset have a shape of (10000, 9) - last column is a target. At first ...
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LSTM Produces Random Predictions

I have trained an LSTM in PyTorch on financial data where a series of 14 values predicts the 15th. I split the data into Train, Test, and Validation sets. I trained the model until the loss ...
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28 views

LSTM predicts variability well, but with underestimating. Regression problem

How can I solve this problem. Model predicts variability well but has a big underestimating Edit 1: I can not give data, sorry. Model: ...
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1answer
22 views

sentiment analysis for multiple entry in one text

I must do sentiment analysis on a set of financial news from s&p500 for given entities (organization names), but the problem is that each news (rows in my dataset) may have more than one entity ...
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1answer
28 views

RNN package and problems with “Predictr”

I have two questions about how to use R's RNN package, specifically the trainr and predictr functions. Let's suppose I have a time series of 4000 steps for 5 different variables. How should this be ...
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37 views

Input and output Dimension of LSTM RNN

I am fairly new to RNNs and Im having trouble setting up the desired output from RNN using Keras library. Each datapoint in my dataset consist of a pattern of labels and timestamp of occurrence of ...
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1answer
34 views

long short term memory in sentiment analysis

I am trying to understand how can long short term memory be used in detecting emotions in dialogues. I would like to know if there are some good tutorials for beginners that I can follow. I watched a ...
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2answers
52 views

How to train LSTM with daily timeseries?

I have for each day sensor timeseries data. I just ask myself how to train with that a LSTM eg. for classification? Since I would like to have the LSTM train on all examples and not just one? I just ...
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1answer
37 views

Predicting on real test set gives only very high probability for 1 for a very unbalanced data

Excuse me for this brief description of the problem, as I'm very bound on time, I'll try to sum up as much as I can. I have a multivariate time-series, that I trained using an RNN, there are periods ...
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1answer
19 views

Which model can solve the “sequence demand” problem?

I have a regression problem. When a truck comes, it influences the demand of employees for the next 30 days. Additionally the demand depends on the type of truck (when the truck is big, we need more ...
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1answer
13 views

Recurrent Neural Networks Over Multiple Documents Over Time

So in my head, I have an idea about what this architecture should look like, or at least behave, but I am having trouble implementing it. So let me describe the problem, and if anyone has an idea on ...
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17 views

How CNN contributes differently in sentiment classification task than RNN?

I would like to know how fundamentally CNN is different from RNN (Many to one) for sentiment classification task. More specifically, what CNN models can learn from data that the RNN can't learn or ...
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14 views

How to group text categorical data basis on clustering?

So if I have text dataset where I have more than 50 categories. Sample: ...
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17 views

Can RNN learn for each `t` in time from a whole new dataset (many entries)

Basically, my data set is not as simple multi-variate time-serie as it's often (to some extent) the case. For each month, I have N entries (not less than 3000). Can RNN of any variant (Please bear my ...
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1answer
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Understanding Exclusive-OR predictions in Elman network

I have been reading Elman network paper, which can be found Here. in page 185, under Exclusive-OR section it was written as follows. Notice that, given the temporal structure of this sequence, it ...
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34 views

Outputs of an LSTM Cell

from each cell of lstm, what are the output's and what does they signify? i understand that there will be three outputs. A long term memory, short term memory and a output. But, i am little confused ...
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Using SMAPE as a loss function for an LSTM

I am currently working on a time series forecasting problem and am looking into using an LSTM. My final accuracy metric that I use to determine whether or not the forecast is good or not is defined ...
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13 views

How to predict multiple iterations in the future based on current close prices? Keras Python

I have data from CoinMarketCap for the close prices of Bitcoin. How can I use this data to predict multiple days into the future using past days with a function? I want the function to look like: <...
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24 views

LSTM/RNN seems to be failing at testing

I'm relatively new to ML, keras and tensorflow and I working with a dataset (kerastest.csv) that is 400 lines of this ...
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48 views

First Neural Network: Poor Quality of Predictions but low val_loss

I am a total newbie to ML, please be gentle :) I've created a RNN that should learn how to count. Input is a sequence of five consecutive numbers N, N+1, ..., N + 4...
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34 views

Can an LSTM learn correlations between time series and produce skillful predictions for individual time series?

I am trying to build a model that is capable of producing a multi-step forecast for many different time series. To keep the example simple, let's say I have three different time series, $T_1$, $T_2$ ...
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1answer
13 views

not quite sure about the difference between RNN and feed forward neural net

I'm a bit confused after reading this paper: https://arxiv.org/abs/1705.09851 on page 22, the author writes response: \begin{equation} Y = softmax(Z^{L-1}) \end{equation} and hidden state \begin{...
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18 views

Multiple entity extraction with character level RNN

I'm training a neural network to extract a certain kind of entities in a sentence (e.g. company names in a news title). Since I'm handling a multi-language corpus (especially CJK), which could be very ...
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1answer
127 views

Give Variable Length input to LSTM

My input data consist of list of list. Both list have dynamic length for every example like below. ...
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1answer
138 views

input_dim for Dense Layer after LSTM layers Keras

Do I need to specify the input_dim (which means the number of features in one row/sample) after adding the first LSTM layer for the later Dense layers? I was trying to create an architecture with 2 ...
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1answer
39 views

No accuracy in Keras RNN Model with Bitcoin Data

I am very new to machine-learning and have made an RNN-LSTM model with no accuracy. My data has been normalized with MinMaxScaler from Sklearn and has a shape of has an input of shape (3, 2)... My ...