Cost-Benefit, Predictive Modeling, Statistics and Uncertainty

Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast. Based on the decisions being made and how quickly plans can adjust to new forecast updates, what is the cost of forecasting too high or too low? If the costs of prediction error are asymmetric (e.g. 95th percentile).

Forecasting

Forecasting Data Science Statistics Uncertainty

Using random effects models in prediction problems

The Unofficial Google Data Science Blog

MARCH 31, 2016

Finally, through a case study of a real-world prediction problem, we also argue that Random Effect models should be considered alongside penalized GLM's even for pure prediction problems. Random effects models are a useful tool for both exploratory analyses and prediction problems.

Modeling

Modeling Statistics Advertising Testing

Data Leaders Brief

Humans-in-the-loop forecasting: integrating data science and business planning

Using random effects models in prediction problems

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