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NumericEnsembles

Automatically Runs 18 Individual and 14 Ensembles of Models

v1.2 · Apr 29, 2026 · MIT + file LICENSE

Description

Automatically runs 18 individual models and 14 ensembles on numeric data, for a total of 32 models. The package automatically returns complete results on all 32 models, 25 charts and six tables. The user simply provides the tidy data, and answers a few questions (for example, how many times would you like to resample the data). From there the package randomly splits the data into train, test and validation sets as the user requests (for example, train = 0.60, test = 0.20, validation = 0.20), fits each of models on the training data, makes predictions on the test and validation sets, measures root mean squared error (RMSE), removes features above a user-set level of Variance Inflation Factor, and has several optional features including scaling all numeric data, four different ways to handle strings in the data. Perhaps the most significant feature is the package's ability to make predictions using the 32 pre trained models on totally new (untrained) data if the user selects that feature. This feature alone represents a very effective solution to the issue of reproducibility of models in data science. The package can also randomly resample the data as many times as the user sets, thus giving more accurate results than a single run. The graphs provide many results that are not typically found. For example, the package automatically calculates the Kolmogorov-Smirnov test for each of the 32 models and plots a bar chart of the results, a bias bar chart of each of the 32 models, as well as several plots for exploratory data analysis (automatic histograms of the numeric data, automatic histograms of the numeric data). The package also automatically creates a summary report that can be both sorted and searched for each of the 32 models, including RMSE, bias, train RMSE, test RMSE, validation RMSE, overfitting and duration. The best results on the holdout data typically beat the best results in data science competitions and published results for the same data set.

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CRAN Check Status

13 OK
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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 9, 2026
ERROR 12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Jun 8, 2026
ERROR r-devel-linux-x86_64-debian-gcc

package dependencies

Packages required but not available: 'car', 'caret', 'olsrr'

Depends: includes the non-default packages:
  'Cubist', 'Metrics', 'arm', 'brnn', 'broom', 'car', 'caret',
  'corrplot', 'doParallel', 'dplyr', 'e1071', 'earth', 'gam', 'gbm',
  'ggplot2',
...[truncated]...
mForest', 'reactable', 'readr', 'rpart', 'scales', 'tidyr',
  'tree', 'xgboost'
Adding so many packages to the search path is excessive and importing
selectively is preferable.

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE May 2, 2026
ERROR 11 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Apr 25, 2026
ERROR r-release-macos-x86_64

package dependencies

Package required but not available: ‘caret’

Depends: includes the non-default packages:
  'Cubist', 'Metrics', 'arm', 'brnn', 'broom', 'car', 'caret',
  'corrplot', 'doParallel', 'dplyr', 'e1071', 'earth', 'gam', 'gbm',
  'ggplot2', 'glmnet', 'gridE
...[truncated]...
', 'reactable', 'readr', 'rpart', 'scales', 'tidyr',
  'tree', 'vip', 'xgboost'
Adding so many packages to the search path is excessive and importing
selectively is preferable.

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
NOTE 11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
NOTE r-oldrel-macos-arm64

package dependencies

Depends: includes the non-default packages:
  'Cubist', 'Metrics', 'arm', 'brnn', 'broom', 'car', 'caret',
  'corrplot', 'doParallel', 'dplyr', 'e1071', 'earth', 'gam', 'gbm',
  'ggplot2', 'glmnet', 'gridExtra', 'htmltools', 'htmlwidgets',
  'ipred', 'leaps', 'nnet', 'olsrr', 'parallel', 'pls', 'purrr',
  'randomForest', 'reactable', 'readr', 'rpart', 'scales', 'tidyr',
  'tree', 'vip', 'xgboost'
Adding so many packages to the search path is excessive and importing
selectively is preferable.
NOTE r-oldrel-macos-x86_64

package dependencies

Depends: includes the non-default packages:
  'Cubist', 'Metrics', 'arm', 'brnn', 'broom', 'car', 'caret',
  'corrplot', 'doParallel', 'dplyr', 'e1071', 'earth', 'gam', 'gbm',
  'ggplot2', 'glmnet', 'gridExtra', 'htmltools', 'htmlwidgets',
  'ipred', 'leaps', 'nnet', 'olsrr', 'parallel', 'pls', 'purrr',
  'randomForest', 'reactable', 'readr', 'rpart', 'scales', 'tidyr',
  'tree', 'vip', 'xgboost'
Adding so many packages to the search path is excessive and importing
selectively is preferable.
NOTE r-oldrel-windows-x86_64

package dependencies

Depends: includes the non-default packages:
  'Cubist', 'Metrics', 'arm', 'brnn', 'broom', 'car', 'caret',
  'corrplot', 'doParallel', 'dplyr', 'e1071', 'earth', 'gam', 'gbm',
  'ggplot2', 'glmnet', 'gridExtra', 'htmltools', 'htmlwidgets',
  'ipred', 'leaps', 'nnet', 'olsrr', 'parallel', 'pls', 'purrr',
  'randomForest', 'reactable', 'readr', 'rpart', 'scales', 'tidyr',
  'tree', 'vip', 'xgboost'
Adding so many packages to the search path is excessive and importing
selectively is preferable.

Dependency Network

Dependencies Reverse dependencies Cubist Metrics arm brnn broom car caret corrplot doParallel dplyr e1071 earth gam gbm ggplot2 +18 more dependencies NumericEnsembles

Version History

11 tracked
updated 1.2 ← 1.0.5 diff Apr 29, 2026
new 1.0.5 Mar 10, 2026
updated 1.0.5 ← 1.0.3 diff Feb 28, 2026
updated 1.0.3 ← 1.0.0 diff Feb 25, 2026
updated 1.0.0 ← 0.10.3 diff Feb 14, 2026
updated 0.10.3 ← 0.10.1 diff Oct 12, 2025
updated 0.10.1 ← 0.9.0 diff Aug 23, 2025
updated 0.9.0 ← 0.8.0 diff Jul 27, 2025
updated 0.8.0 ← 0.7.0 diff May 31, 2025
updated 0.7.0 ← 0.5.0 diff Apr 9, 2025
new 0.5.0 Mar 31, 2025