final_models: Final Models

In microsoft/finnts: Microsoft Finance Time Series Forecasting Framework

Final Models

Description

Select Best Models and Prep Final Outputs

Usage

final_models(
  run_info,
  average_models = TRUE,
  max_model_average = 3,
  weekly_to_daily = TRUE,
  parallel_processing = NULL,
  inner_parallel = FALSE,
  num_cores = NULL
)

Arguments

run_info	run info using the set_run_info() function.
average_models	If TRUE, create simple averages of individual models and save the most accurate one.
max_model_average	Max number of models to average together. Will create model averages for 2 models up until input value or max number of models ran.
weekly_to_daily	If TRUE, convert a week forecast down to day by evenly splitting across each day of week. Helps when aggregating up to higher temporal levels like month or quarter.
parallel_processing	Default of NULL runs no parallel processing and forecasts each individual time series one after another. 'local_machine' leverages all cores on current machine Finn is running on. 'spark' runs time series in parallel on a spark cluster in Azure Databricks or Azure Synapse.
inner_parallel	Run components of forecast process inside a specific time series in parallel. Can only be used if parallel_processing is set to NULL or 'spark'.
num_cores	Number of cores to run when parallel processing is set up. Used when running parallel computations on local machine or within Azure. Default of NULL uses total amount of cores on machine minus one. Can't be greater than number of cores on machine minus 1.

Value

Final model outputs are written to disk.

Examples

data_tbl <- timetk::m4_monthly %>%
  dplyr::rename(Date = date) %>%
  dplyr::mutate(id = as.character(id)) %>%
  dplyr::filter(
    Date >= "2013-01-01",
    Date <= "2015-06-01"
  )

run_info <- set_run_info()

prep_data(run_info,
  input_data = data_tbl,
  combo_variables = c("id"),
  target_variable = "value",
  date_type = "month",
  forecast_horizon = 3
)

prep_models(run_info,
  models_to_run = c("arima", "ets"),
  back_test_scenarios = 3
)

train_models(run_info,
  run_global_models = FALSE
)

final_models(run_info)

microsoft/finnts documentation built on Oct. 30, 2024, 9:34 p.m.