Forecasting
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
Forecasting Potential Misuses of Language Models for Disinformation Campaigns—and The right way to Reduce Risk
OpenAI researchers collaborated with Georgetown University’s Center for Security and Emerging Technology and the Stanford Web Observatory to analyze how large language models may be misused...
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