5
votes
Could you explain if this plot is good or bad. It is a sentiment analysis modelusing LSTM layers
"Good" or "bad" is always relative in data science. You need to establish a benchmark for comparison.
First of all, you need to know that accuracy is not a very good performance ...
- 153
2
votes
Could you explain if this plot is good or bad. It is a sentiment analysis modelusing LSTM layers
It is not a good plot because:
The axis lack labels.
The legend labels are not very meaningful, "Validation" and "Test" would be better choices.
The plot relies solely on color to ...
- 121
2
votes
How to arrange multiple multivariate time series of different length before passing it to Keras LSTM layer
To use multiple multivariate time series with different lengths and timestamps as input to a Keras LSTM model, you can follow these steps:
Pad the time series to the same length: You can pad each ...
- 319
1
vote
Accepted
Why are the hidden states of an RNN initialised every epoch instead of every batch?
Hidden states of an RNN are initialized every epoch ONLY if you are using truncated back-propagation through time (TBPTT).
If you are not using TBPTT, then you would reset the RNN hidden states at ...
- 17.4k
1
vote
LSTMs how to forecast out N steps
So this is what I have to predict 96 samples into the future which is 24 hours 15 minutes at a crack:
...
- 371
1
vote
Using the whole GloVe pre-trained embedding matrix or minimize the matrix based on the number of words in vocabulary
Long Short Term Memory (LSTM) can take a long time to train because of the complexity of the architecture.
If you think the size of the embedding space is also slowing down training, you can reduce ...
- 18.6k
1
vote
Could you explain if this plot is good or bad. It is a sentiment analysis modelusing LSTM layers
It's a fairly good looking plot but it seems like your model if slightly overfitting to the train_dataset
- 23
1
vote
Are there any practical advantages of LSTMs over transformers?
LSTMs/GRUs have lower computational and memory requirements than transformers.
Depending on the case, using an LSTM instead of a Transformer may make sense due to those factors. For instance, using ...
- 17.4k
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