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Include information about model performance in easier to access format

Abierto
  • ¿Algo no está bien?
#3 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
35/100
Tipo de issue
Nueva funcionalidad
Claridad
Necesita aclaración
Estado de actividad
Estancado
Stack tecnológico
python
Área
data, machine-learning

Línea de trabajo

Start by examining the existing data components and the general to_df() output to understand which forecast, observed, detrended, holiday, country, and date values are already available. Compare that structure with the proposed performance_df() option and the listed analysis questions. Done means a consistent DataFrame format exposes the requested absolute and relative comparisons, with its intended scope distinguished from Prophet's performance_metrics.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

I think this is something that can be calculated from existing data components, but might not currently be packaged up in one consistent format.

Here were some of the analysis questions I encountered that I could not immediately figure out how to address with the current data structure:

  • Was the effect of X holiday larger or smaller this year than prior year(s)? By how much? (In absolute count and in relative percent)
  • When comparing trends (i.e. across multiple dates), is the gap between forecast and observed growing, shrinking, or staying level?
    • E.g., if a model underestimated holiday impact, do the trends re-converge in the following days or does that gap persist as a step-change?
  • Within each country/population, how far off was the forecast value from the observed value on a given date? (In absolute count and relative percent)
  • What exactly was the impact of holiday(s) on the forecast value for a given date? (In absolute count and relative percent)
    • This may just be the difference between the detrended forecast and the final forecast.
  • What was the estimated impact of holiday(s) on a historical observed value for a given date? (In absolute count and relative percent)
    • This may just be the difference between the detrended amount and the observed amount.

Ideally, this could be included in a simple DataFrame -- either as additional columns in the same general DataFrame output from the general to_df() function, or maybe as a separate dedicated function for performance_df().

(Also acknowledging that this might be different than some other object that stores overall measures of model performance -- things that might come out of Prophet's performance_metrics).

Lenguaje dominante
Python
Estrellas
3
Forks
3
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Primeros pasos

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  4. Abre un pull request que haga referencia al número del issue.

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