Questions tagged [long-short-term-memory]

For questions related to the long-short term memory (LSTM), which refers to a recurrent neural network architecture that uses LSTM units. The first LSTM unit was proposed in 1997 by Sepp Hochreiter and Jürgen Schmidhuber in the paper "Long-Short Term Memory".

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Learning from events. Supervised, Unsupervised or MDP?

I have a large set of simulation logs for a market simulation of which I want to learn from. The market includes: customers products (subscriptions) The customers choose products and then stick with ...
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25 views

Outliers detection problem in neural networks

Assuming we have big m x n input dataset with m x 1 output vector. It's a classification problem with only two possible values: either 1 or 0. Now the problem is that almost all elements of the output ...
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23 views

Why is the value range of my LSTM model's prediction different from my test labels?

I am using LSTM to do time-series anomaly detection. The data is an hourly sensor input across multiple years (i.e. the global_active_energy attribute of the dataset from https://www.kaggle.com/uciml/...
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Make an LSTM model for each class separately

I have a dataset of some activities. The dataset contains the status of different sensors and the label of activity. T trained a model in Keras with the following architecture which models the ...
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42 views

Preparation of input data

Tell me why my val_acc is always the same and how to solve this problem? I saw several topics on the Internet specifically on this problem but they did not help me (for example, use SGD with different ...
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1answer
66 views

How to train a LSTM model with multi dimensional data

I am trying to train my model using LTSM layer in Keras (python). I have some problems regarding the data representation and feeding it into the model. My data is 184 XY coodinates encoded as a numpy ...
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55 views

Why doesnt my lstm model for time series prediction improve after certain level of performance?

I created an lstm model which predicts multioutput sequeances. It takes variable length sequences as input. These sequences are padded with zero to obtain equal length. Note that the time series are ...
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23 views

Custom optimizer and word-vector evaluator lstm

I’m using Keras LSTM layers and building a model that is trained off ethics text. I have a problem of often over fitting (the network basically remembers my input corpus as it is very small). I was ...
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130 views

How Seq2Seq with Bidirectional RNN works?

First of all the scope of the question is as follows - we have Sequence2Sequence architecture with: Decoder: Bidirectional LSTM Encoder: regular (single directional) LSTM What I know: When you ...
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115 views

Details of implementing an LSTM in Reinforcement Learning

I'm currently looking into the context of adding an LSTM to my PPO pytorch implementation. My plan is to add one LSTM layer right after the last convolutional layer. I'm wondering now whether it is ...
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40 views

Unsupervised LSTM

I have a big amount of light curves (image below) and I am trying to label the points as signal or background (the signal appears usually periodically, several times, for a given light curve). However,...
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19 views

Benefits in using multiple LSTM layers?

I am working on a time series forecasting problem and I am in the process of choosing the optimum network structure. Currently I have a 200 cell LSTM layer fully connected to 100 neurons in an ...
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182 views

Error using Keras clear_session while multiple calibration

I am working through the tutorial here. I just cleaned up the code for myself but other than that code is as in original tutorial. I am using the pollution data from the following link When I try to ...