modeltime 1.3.0

Overview

This version and modeltime 1.2.8 (previous version) include changes to incorporate Conformal Prediction Intervals. There are a number of changes that include new "conformal" confidence methods and Tibble (Data Frame) table display improvements of forecasts aimed at helping the user understand what confidence method is being used and the confidence interval being used throughout the forecasting process in both Standard and Nested Modeltime Forecasting Workflows.

Conformal Predictions:

• Integrate Conformal Predictions into Nested Forecast Workflow: modeltime_nested_fit() and modeltime_nested_refit(). #173
• Updated the print display for conformal prediction Conf Method, Conf Interval:
  • modeltime_forecast()
  • extract_nested_test_forecast()
  • extract_nested_future_forecast()
  • modeltime_nested_forecast()

Other Changes:

• Dials Parameters: Remove deprecated default inside new_qual_param().
• Fix warning in dev-xregs: Use all_of() inside prepare_xreg_recipe_from_predictors()
• Fix broken test: test-tune_workflows Unused argument: cores = 2

modeltime 1.2.8

• Integrate Conformal Predictions. #173
• New Vignette: Conformal Forecast Prediction Intervals in Modeltime

Other Changes:

• Reduced test times on CRAN
• CRAN Vignettes & Tests: Enforce no parallel cores Sys.setenv("OMP_THREAD_LIMIT" = 1)
• Change the default parallel processing to one (1) core from all available cores (-1):
  • control_refit()
  • control_fit_workflowset()
  • control_nested_fit()
  • control_nested_refit()
  • control_nested_forecast()

modeltime 1.2.5

• Fixes for Smooth es() model #221

Fix failing tests in test-developer-tools-xregs.R

• Recursive chunk_size (performance improvement) #197 #190
• Recursive model fixes #194, #188, #187, #174
• New function, drop_modeltime_model #160
• Updates for workflows mode = "regression"

modeltime 1.2.2

Fixes

• Updates for hardhat 1.0.0 #182

modeltime 1.2.1

Trelliscope Plotting

• plot_modeltime_forecast(): Expose the facet_trelliscope() plotting parameters.

Fixes

• Use step_rm() to get rid of date rather than updating its role #181

New Features

Many of the plotting functions have been upgraded for use with trelliscopejs for easier visualization of many time series.

• plot_modeltime_forecast():
  • Gets a new argument trelliscope: Used for visualizing many time series.
  • Gets a new argument .facet_strip_remove to remove facet strips since trelliscope is automatically labeled.
  • Gets a new argument .facet_nrow to adjust grid with trelliscope.
  • The default argument for facet_collapse = TRUE was changed to FALSE for better compatibility with Trelliscope JS. This may cause some plots to have multiple groups take up extra space in the strip.

Fixes

• Fixes issue of incorrect order of forecasts #142

Spark Backend

• Modeltime now has a Spark Backend

• NEW Vignette - Modeltime Spark Backend describing how to set up Modeltime with the Spark Backend.

New Algorithms: Smooth Package Integration

If users install smooth, the following models become available:

• adam_reg(): Interfaces with the ADAM forecasting algorithm in smooth.

• exp_smoothing(): A new engine "smooth_es" connects to the Exponential Smoothing algorithm in smooth::es(). This algorithm has several advantages, most importantly that it can use x-regs (unlike "ets" engine).

Nested Modeltime Improvements

• New extractor: extract_nested_modeltime_table() - Extracts a nested modeltime table by row id.

Breaking Changes (potentially)

• extract_nested_train_split and extract_nested_test_split: Changed parameter from .data to .object for consistency with other "extract" functions

• Added a new logged feature to modeltime_nested_fit() to track the attribute "metric_set", which is needed for ensembles. Old nested modeltime objects will need to be re-run to get this new attribute. This will be used in ensembles.