All Questions
Tagged with neural-networkrnn
229 questions
2votes
0answers
21views
Do i.i.d. assumptions extend to datasets of independently generated sequences in modern sequence models (e.g., RNNs)?
In standard machine learning settings with cross-sectional data, it's common to assume that data points are independently and identically distributed (i.i.d.) from some fixed data-generating process (...
- 101
0votes
0answers
13views
What's the best model for hourly energy consumption?
I have a dataset of hourly energy consumption from a building from 2010 to 2015. With normal NN I am reaching ~94% accuracy. Didn't try yet with other types of models. Should I try CNN? RNN? ...
0votes
0answers
21views
RNN / LSTM Network for Forecasting Multidimensional Time Series
I have data daily time series from products consumed in a hotel. I got 30 time series of the product consumption (target variable) and bunch of explanatory variables for each product and related to ...
- 11
1vote
0answers
35views
How to choose a neural network architecture?
How to choose a neural network architecture? Examples: «What if I need to translate words?» «Generate text, images?» «Play a regular game?» «Play a game that changes depending on the player's actions, ...
1vote
0answers
46views
ML. How to make a neural network remember the context and data?
I want the neural network to be able to remember, but a perceptron can only remember something during training, but I want the neural network to adapt to new conditions without retraining, for example,...
0votes
0answers
18views
Semantics Building In LSTM-Based Models - How does a LSTM is able to extract and represent long data using just one value (long-memory)
How does a LSTM is able to extract and represent long sequences with data while using just one value (long-memory / LM) to maintain all this information? If multiple value were used, it could be ...
0votes
0answers
14views
Deep neural network is plateauing on a regression task
I'm training a deep neural network on temporal graph data. Currently, I'm trying to get a feel for how large / complex of a model I should aim for, so I'm trying to overfit to my smallest dataset. ...
0votes
1answer
113views
Connecting Flatten layer to Dense layer
I'm struggling with my neural network. In short, I need to recreate a model from anywhere on the internet, I've found a model that combines BiLSTM, LSTM and GRU. However, based on the error I got when ...
1vote
1answer
77views
Why my validation loss and accuracy decays over epochs?
Im trying to build 2 simple networks with cleaned dataset for tweets sentiment classification(0/1): one with all dense layers(binary bag of words) another with RNN layer(embedding layer). But it both ...
- 35
1vote
0answers
63views
LSTM for classification
I am new to neural networks and I want to use LSTM to classify the on/off state of devices based on power values. In my training dataset, I have power values, device one (0,1), and device 2 (0,1). 0 ...
- 11
0votes
1answer
72views
Confusion regarding what constitutes a feature in a LSTM?
I have a Time Series problem, where I am trying to predict a single output at time $t$, $y_t$, given the $2$ previous time steps; $X_{t-2}, X_{t-1}$. Let's just look at one observation for simplicity. ...
- 157
5votes
2answers
382views
Modeling uncertainty from known physics
I have an equation given by: $$ \frac{\mathrm{d} s}{\mathrm{d} t}=4a−2s+\lambda(s) $$ where, $a$ is an input constant and $\lambda$ is a non-linear term that depends on $s$. I know that the true ...
user149991
0votes
1answer
76views
Why is a RNN inherently better for Time series than normal NN?
Similar to this question but I would like further clarification. I understand that in abstract, RNNs can process inputs recursively and feed some state of memory through the recursion to have a sense ...
1vote
1answer
221views
How is RNN decoder output calculated?
I was trying to read RNN Encoder Decoder paper. RNN (plain RNN i.e. non encoder-decoder RNN) It starts with giving equation for RNN: hidden state in RNN is given as: ... equation (1) where f is a ...
- 299
0votes
0answers
47views
Input size vs hidden state in RNNs
Im using PyTorch to implement RNNs on univariate time series data. This is the documentation for the RNN class: link I think I'm understanding the math behind an RNN cell. But I have an specific ...
- 101
