## "Fossies" - the Fresh Open Source Software Archive

### Source code changes of the file "R/man/performance_metrics.Rd" betweenprophet-0.7.tar.gz and prophet-1.0.tar.gz

About: Prophet is a tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

performance_metrics.Rd  (prophet-0.7):performance_metrics.Rd  (prophet-1.0)
skipping to change at line 13 skipping to change at line 13
\name{performance_metrics} \name{performance_metrics}
\alias{performance_metrics} \alias{performance_metrics}
\title{Compute performance metrics from cross-validation results.} \title{Compute performance metrics from cross-validation results.}
\usage{ \usage{
performance_metrics(df, metrics = NULL, rolling_window = 0.1) performance_metrics(df, metrics = NULL, rolling_window = 0.1)
} }
\arguments{ \arguments{
\item{df}{The dataframe returned by cross_validation.} \item{df}{The dataframe returned by cross_validation.}
\item{metrics}{An array of performance metrics to compute. If not provided, \item{metrics}{An array of performance metrics to compute. If not provided,
will use c('mse', 'rmse', 'mae', 'mape', 'mdape', 'coverage').} will use c('mse', 'rmse', 'mae', 'mape', 'mdape', 'smape', 'coverage').}
\item{rolling_window}{Proportion of data to use in each rolling window for \item{rolling_window}{Proportion of data to use in each rolling window for
computing the metrics. Should be in [0, 1] to average.} computing the metrics. Should be in [0, 1] to average.}
} }
\value{ \value{
A dataframe with a column for each metric, and column 'horizon'. A dataframe with a column for each metric, and column 'horizon'.
} }
\description{ \description{
Computes a suite of performance metrics on the output of cross-validation. Computes a suite of performance metrics on the output of cross-validation.
By default the following metrics are included: By default the following metrics are included:
'mse': mean squared error, 'mse': mean squared error,
'rmse': root mean squared error, 'rmse': root mean squared error,
'mae': mean absolute error, 'mae': mean absolute error,
'mape': mean percent error, 'mape': mean percent error,
'mdape': median percent error, 'mdape': median percent error,
'smape': symmetric mean absolute percentage error,
'coverage': coverage of the upper and lower intervals 'coverage': coverage of the upper and lower intervals
} }
\details{ \details{
A subset of these can be specified by passing a list of names as the A subset of these can be specified by passing a list of names as the
metrics argument. metrics argument.
Metrics are calculated over a rolling window of cross validation Metrics are calculated over a rolling window of cross validation
predictions, after sorting by horizon. Averaging is first done within each predictions, after sorting by horizon. Averaging is first done within each
value of the horizon, and then across horizons as needed to reach the value of the horizon, and then across horizons as needed to reach the
window size. The size of that window (number of simulated forecast points) window size. The size of that window (number of simulated forecast points)
End of changes. 2 change blocks.
1 lines changed or deleted 2 lines changed or added