CRAN Package Check Results for Package modeltime.ensemble

Last updated on 2021-01-26 07:50:21 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.3.0 17.09 302.30 319.39 OK
r-devel-linux-x86_64-debian-gcc 0.3.0 14.54 223.05 237.59 OK
r-devel-linux-x86_64-fedora-clang 0.3.0 376.22 NOTE
r-devel-linux-x86_64-fedora-gcc 0.3.0 383.84 NOTE
r-devel-windows-ix86+x86_64 0.3.0 44.00 337.00 381.00 OK
r-patched-linux-x86_64 0.3.0 12.82 288.75 301.57 OK
r-patched-solaris-x86 0.3.0 2124.20 ERROR
r-release-linux-x86_64 0.3.0 12.48 290.44 302.92 OK
r-release-macos-x86_64 0.3.0 NOTE
r-release-windows-ix86+x86_64 0.3.0 44.00 258.00 302.00 OK
r-oldrel-macos-x86_64 0.3.0 NOTE
r-oldrel-windows-ix86+x86_64 0.3.0 35.00 306.00 341.00 OK

Check Details

Version: 0.3.0
Check: package dependencies
Result: NOTE
    Imports includes 22 non-default packages.
    Importing from so many packages makes the package vulnerable to any of
    them becoming unavailable. Move as many as possible to Suggests and
    use conditionally.
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.3.0
Check: dependencies in R code
Result: NOTE
    Namespaces in Imports field not imported from:
     ‘crayon’ ‘dials’ ‘glmnet’ ‘parsnip’ ‘progressr’ ‘utils’
     All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86, r-release-macos-x86_64, r-oldrel-macos-x86_64

Version: 0.3.0
Check: tests
Result: ERROR
     Running ‘testthat.R’ [30m/31m]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     >
     > # Machine Learning
     > library(tidymodels)
     ── Attaching packages ────────────────────────────────────── tidymodels 0.1.2 ──
     ✔ broom 0.7.3 ✔ recipes 0.1.15
     ✔ dials 0.0.9 ✔ rsample 0.0.8
     ✔ dplyr 1.0.3 ✔ tibble 3.0.5
     ✔ ggplot2 3.3.3 ✔ tidyr 1.1.2
     ✔ infer 0.5.4 ✔ tune 0.1.2
     ✔ modeldata 0.1.0 ✔ workflows 0.2.1
     ✔ parsnip 0.1.5 ✔ yardstick 0.0.7
     ✔ purrr 0.3.4
     ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
     ✖ purrr::discard() masks scales::discard()
     ✖ dplyr::filter() masks stats::filter()
     ✖ purrr::is_null() masks testthat::is_null()
     ✖ dplyr::lag() masks stats::lag()
     ✖ tidyr::matches() masks dplyr::matches(), testthat::matches()
     ✖ recipes::step() masks stats::step()
     > library(modeltime)
     > library(modeltime.ensemble)
     Loading required package: modeltime.resample
     > library(modeltime.resample)
     >
     > library(xgboost)
    
     Attaching package: 'xgboost'
    
     The following object is masked from 'package:dplyr':
    
     slice
    
     >
     > # Core Packages
     > library(tidyverse)
     ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
     ✔ readr 1.4.0 ✔ forcats 0.5.0
     ✔ stringr 1.4.0
     ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
     ✖ readr::col_factor() masks scales::col_factor()
     ✖ purrr::discard() masks scales::discard()
     ✖ dplyr::filter() masks stats::filter()
     ✖ stringr::fixed() masks recipes::fixed()
     ✖ purrr::is_null() masks testthat::is_null()
     ✖ dplyr::lag() masks stats::lag()
     ✖ tidyr::matches() masks dplyr::matches(), testthat::matches()
     ✖ xgboost::slice() masks dplyr::slice()
     ✖ readr::spec() masks yardstick::spec()
     > library(timetk)
     > library(lubridate)
    
     Attaching package: 'lubridate'
    
     The following objects are masked from 'package:base':
    
     date, intersect, setdiff, union
    
     >
     > test_check("modeltime.ensemble")
     ── Modeltime Ensemble ───────────────────────────────────────────
     Ensemble of 3 Models (MEDIAN)
    
     # Modeltime Table
     # A tibble: 3 x 3
     .model_id .model .model_desc
     <int> <list> <chr>
     1 1 <workflow> ARIMA(0,1,1)(0,1,1)[12]
     2 2 <workflow> PROPHET
     3 3 <workflow> GLMNET
     ── Fitting Non-Tunable Model Specification ──────────────────────
    
     # A tibble: 4 x 3
     .model_id rmse .model_desc
     <chr> <dbl> <chr>
     1 1 579. ARIMA(0,1,1)(0,1,1)[12]
     2 2 381. PROPHET
     3 3 558. GLMNET
     4 ensemble 128. ENSEMBLE (MODEL SPEC)
    
     ── Final Model ──────────────────────────────────────────────────
    
     ══ Workflow [trained] ══════════════════════════════════════════════════════════
     Preprocessor: Recipe
     Model: linear_reg()
    
     ── Preprocessor ────────────────────────────────────────────────────────────────
     0 Recipe Steps
    
     ── Model ───────────────────────────────────────────────────────────────────────
    
     Call:
     stats::lm(formula = ..y ~ ., data = data)
    
     Coefficients:
     (Intercept) .model_id_1 .model_id_2 .model_id_3
     -2637.2266 0.5754 -0.1919 0.8550
    
    
     1.378 sec elapsed
    
     ── Modeltime Ensemble ───────────────────────────────────────────
     Ensemble of 3 Models (LM STACK)
    
     # Modeltime Table
     # A tibble: 3 x 3
     .model_id .model .model_desc
     <int> <list> <chr>
     1 1 <workflow> ARIMA(0,1,1)(0,1,1)[12]
     2 2 <workflow> PROPHET
     3 3 <workflow> GLMNET
     ── Modeltime Ensemble ───────────────────────────────────────────
     Ensemble of 3 Models (GLMNET STACK)
    
     # Modeltime Table
     # A tibble: 3 x 3
     .model_id .model .model_desc
     <int> <list> <chr>
     1 1 <workflow> ARIMA(0,1,1)(0,1,1)[12]
     2 2 <workflow> PROPHET
     3 3 <workflow> GLMNET
     ── Modeltime Ensemble ───────────────────────────────────────────
     Ensemble of 3 Models (WEIGHTED)
    
     # Modeltime Table
     # A tibble: 3 x 4
     .model_id .model .model_desc .loadings
     <int> <list> <chr> <dbl>
     1 1 <workflow> ARIMA(0,1,1)(0,1,1)[12] 0.5
     2 2 <workflow> PROPHET 0.333
     3 3 <workflow> GLMNET 0.167
Flavor: r-patched-solaris-x86