All Questions
10 questions
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19
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How does highly imbalanced test data in certain splits of k-fold time-series cross-validation affect model performance?
I am working on a time-series classification (TSC) problem using k-fold time-series cross-validation (TSCV) to evaluate the performance of my models. My training data for each split is fairly balanced,...
2
votes
1
answer
149
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How to handle hyperparameter tuning for LSTM with early stopping?
I am looking for advice on the best practice to determine hyperparameters for my LSTM model. I have time series data that I have divided into train and test sets. I was planning to use an expanding ...
- 255
2
votes
1
answer
136
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Time Series Split Validation When Certain Time Display Unique Characteristics
Since my data is a time series, I've been using an expanding window walk forward validation via Sklearn's TimeSeriesSplit() to tune the hyper-parameters of my NN. ...
- 123
0
votes
0
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238
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Time series data validation error is significantly lower than training error
I have a time series dataset that covers daily observations (closing price) for several stocks, and I would like to build models to forecast the closing prices for the future 7 days using their ...
- 1
0
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0
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462
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How to forecast with ARIMA + neural network?
I am working on a real life problem of forecasting 3 days sales for a retail store. I am thinking of applying a hybrid model (ARIMAX+Neural network) i.e. Dynamic regression with regressors using ...
2
votes
2
answers
704
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Time series cross validation by reversing the series
I am trying to forecast revenue of a company, using neural networks. The response is a time series of monthly revenues from 11/2008 to 05/2016, and there are about 45 predictors (including lagged ...
- 23
4
votes
0
answers
2k
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Using AIC or cross-validated MSE for selecting neural network models for time series prediction
I trained two basic feed-forward neural networks on time series data. The first one uses the observation at time step $t$ to predict $t+1$. Hence, it only has one predictor variable. The second ...
- 3,112
1
vote
1
answer
605
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Train neural network for forecasting
I am trying to use time series neural network to predict future values. I have time series data from 2010-2014 and I need to predict the values from 2015-2020 using time series neural network. I am ...
3
votes
1
answer
2k
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Cross-validation with neural networks yielding worse results than a standard neural network
Summary: when using a 10-fold cross-validation procedure where each training set is used to generate N bootstrap samples for processing with NNs. How do I provide my NN with correct sequence and ...
- 233
8
votes
3
answers
3k
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k-fold CV of forecasting financial time series -- is performance on last fold more relevant?
I am working on an ANN-based forecasting model for a financial time series. I'm using 5-fold cross-validation and the average performance is so so. Performance on the last fold (the iteration where ...
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