Series
Artificial Intelligence
Model Evaluation in Time Series Forecasting
Introducing backtesting for time series using the Skforecast libraryBelow, there are the three described backtesting methods with a random forest regressor used as autoregression.When taking a look at the implementation, the difference between the...
Artificial Intelligence
Time Series Forecasting with XGBoost and LightGBM: Predicting Energy Consumption Problem Preprocessing Training the Models Evaluation Preprocessing Weather Data Conclusion & Future Steps
The weather data improve the performance in each models by a major margin. Particularly, within the XGBoost scenario the MAE is reduced by almost 44%, while the MAPE moved from 19% to 16%. For...
Artificial Intelligence
Earth Mover distance for time series
WWhilst many metrics corresponding to MAPE, MAE and RMSE exist for evaluating forecasting performance, such metrics have significant limitations as they only compare forecast values with actual values for a similar closing dates.For a...
Artificial Intelligence
Jorge Torres, Co-founder & CEO of MindsDB – Interview Series
Jorge Torres, is the Co-founder & CEO of MindsDB, a platform that helps anyone use the ability of machine learning to ask predictive questions of their data and receive accurate answers from it. MindsDB...
Artificial Intelligence
Transform Time Series for Deep Learning Supervised Learning with Time Series Auto-Regression with Deep Learning Hands-On Key Takeaways
Forecasting with deep neural networksThe forecasts aren't that good. The time series is small and we didn’t optimize the model in any way. Deep learning methods are known to be data-hungry. So, in case...
Artificial Intelligence
Easy methods to Transform Time Series for Deep Learning Supervised Learning with Time Series Auto-Regression with Deep Learning Hands-On Key Takeaways
Forecasting with deep neural networksThe forecasts will not be that good. The time series is small and we didn’t optimize the model in any way. Deep learning methods are known to be data-hungry. So,...
Artificial Intelligence
Transform Time Series for Deep Learning Supervised Learning with Time Series Auto-Regression with Deep Learning Hands-On Key Takeaways
Forecasting with deep neural networksThe forecasts should not that good. The time series is small and we didn’t optimize the model in any way. Deep learning methods are known to be data-hungry. So, for...
Artificial Intelligence
The best way to Transform Time Series for Deep Learning
Forecasting with deep neural networksThe forecasts usually are not that good. The time series is small and we didn’t optimize the model in any way. Deep learning methods are known to be data-hungry. So,...
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