missRanger

Fast multivariate imputation by random forests.

https://github.com/mayer79/missranger

Science Score: 39.0%

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Low similarity (12.3%) to scientific vocabulary

Keywords

imputation machine-learning missing-values r random-forest rstats

Last synced: 6 months ago · JSON representation

Repository

Fast multivariate imputation by random forests.

Basic Info

Host: GitHub
Owner: mayer79
License: gpl-2.0
Language: R
Default Branch: main
Homepage: https://mayer79.github.io/missRanger/
Size: 12.9 MB

Statistics

Stars: 70
Watchers: 10
Forks: 11
Open Issues: 2
Releases: 9

Topics

imputation machine-learning missing-values r random-forest rstats

Created over 9 years ago · Last pushed 11 months ago

Metadata Files

Readme Changelog License

{missRanger}

Overview

{missRanger} is a multivariate imputation algorithm based on random forests. It is a fast alternative to the famous 'MissForest' algorithm (Stekhoven and Buehlmann, 2012), and uses the {ranger} package (Wright and Ziegler, 2017) to fit the random forests. Since version 2.6.0, out-of-sample application is possible.

Installation

```r

From CRAN

install.packages("missRanger")

Development version

devtools::install_github("mayer79/missRanger") ```

Usage

```r library(missRanger)

set.seed(3)

irisNA <- generateNA(iris, p = 0.1) head(irisNA)

Sepal.Length Sepal.Width Petal.Length Petal.Width Species

5.1 3.5 1.4 0.2 setosa

4.9 3.0 1.4 NA setosa

4.7 3.2 1.3 0.2 setosa

4.6 3.1 1.5 0.2

NA 3.6 1.4 0.2 setosa

5.4 3.9 1.7 0.4

irisfilled <- missRanger(irisNA, pmm.k = 5, num.trees = 100) head(iris_filled)

Sepal.Length Sepal.Width Petal.Length Petal.Width Species

1 5.1 3.5 1.4 0.2 setosa

2 4.9 3.0 1.4 0.2 setosa

3 4.7 3.2 1.3 0.2 setosa

4 4.6 3.1 1.5 0.2 setosa

5 5.2 3.6 1.4 0.2 setosa

6 5.4 3.9 1.7 0.4 setosa

```

How it works

The algorithm iterates until the average out-of-bag (OOB) error of the forests stops improving. The missing values are filled by OOB predictions of the best iteration, optionally followed by predictive mean matching (PMM). The PMM step avoids values not present in the original data (like a value 0.3334 in a 0-1 coded variable). Furthermore, PMM raises the variance in the resulting conditional distributions to a more realistic level, a crucial property for multiple imputation.

Check-out the vignettes for more info, and for how to use missRanger() in multiple imputation.

References

Stekhoven D. J., Buehlmann, P. (2012). MissForest - non-parametric missing value imputation for mixed-type data. Bioinformatics, 28(1), 112-118.
Marvin N. Wright, Andreas Ziegler (2017). ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R. Journal of Statistical Software, 77(1), 1-17. doi:10.18637/jss.v077.i01

Owner

Name: Michael Mayer
Login: mayer79
Kind: user

Repositories: 12
Profile: https://github.com/mayer79

Responsible statistics | ML

GitHub Events

Total

Create event: 4
Release event: 1
Issues event: 8
Watch event: 4
Delete event: 4
Issue comment event: 5
Push event: 10
Pull request event: 6

Last Year

Create event: 4
Release event: 1
Issues event: 8
Watch event: 4
Delete event: 4
Issue comment event: 5
Push event: 10
Pull request event: 6

Committers

Last synced: 9 months ago

All Time

Total Commits: 213
Total Committers: 8
Avg Commits per committer: 26.625
Development Distribution Score (DDS): 0.221

Past Year

Commits: 74
Committers: 1
Avg Commits per committer: 74.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
Michael Mayer	m**9@g**m	166
Michael Mayer	m**r@c**h	31
MMA	M**A@I**L	8
olivroy	5****y	4
Thierry Gosselin	t**n@i**m	1
Jamey McDowell	j**l@g**m	1
Andrew Landgraf	a****d	1
MMA	M**A@n**2	1

Committer Domains (Top 20 + Academic)

consultag.ch: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time

Total issues: 42
Total pull requests: 44
Average time to close issues: 3 months
Average time to close pull requests: about 16 hours
Total issue authors: 28
Total pull request authors: 6
Average comments per issue: 2.33
Average comments per pull request: 0.64
Merged pull requests: 41
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 8
Pull requests: 18
Average time to close issues: 12 days
Average time to close pull requests: about 20 hours
Issue authors: 5
Pull request authors: 1
Average comments per issue: 1.75
Average comments per pull request: 0.28
Merged pull requests: 18
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

mayer79 (8)
thierrygosselin (5)
DarioS (3)
bgall (2)
jeandigitale (1)
lime-n (1)
ldliao (1)
AurelieMich (1)
LouChen-med (1)
stephematician (1)
joannawolthuis (1)
visokie (1)
NamLQ (1)
James-Yong-XIANG (1)
JameyPMcDowell (1)

Pull Request Authors

mayer79 (53)
pdwaggoner (3)
olivroy (2)
thierrygosselin (1)
JameyPMcDowell (1)
andland (1)

Top Labels

Issue Labels

enhancement (7) bug (4) documentation (2) wontfix (2) question (1)

Pull Request Labels

bug (2) enhancement (2)

Packages

Total packages: 1
Total downloads:
- cran 2,724 last-month
Total docker downloads: 42,128

Total dependent packages: 7
Total dependent repositories: 13
Total versions: 16
Total maintainers: 1

cran.r-project.org: missRanger

Fast Imputation of Missing Values

Homepage: https://github.com/mayer79/missRanger
Documentation: http://cran.r-project.org/web/packages/missRanger/missRanger.pdf
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Latest release: 2.6.1
published about 1 year ago

Versions: 16
Dependent Packages: 7
Dependent Repositories: 13
Downloads: 2,724 Last month
Docker Downloads: 42,128

Rankings

Docker downloads count: 0.6%

Downloads: 5.4%

Average: 5.5%

Stargazers count: 6.3%

Forks count: 6.3%

Dependent packages count: 6.6%

Dependent repos count: 8.0%

Maintainers (1)

mayermichael79@gmail.com

Last synced: 6 months ago

Dependencies

DESCRIPTION cran

R >= 3.5.0 depends
FNN * imports
ranger * imports
stats * imports
utils * imports
dplyr * suggests
knitr * suggests
mice * suggests
rmarkdown * suggests
survival * suggests
testthat >= 3.0.0 suggests

.github/workflows/R-CMD-check.yaml actions

actions/checkout v3 composite
r-lib/actions/check-r-package v2 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/pkgdown.yaml actions

JamesIves/github-pages-deploy-action v4.4.1 composite
actions/checkout v3 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/test-coverage.yaml actions

actions/checkout v3 composite
actions/upload-artifact v3 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

missRanger

Science Score: 39.0%

Keywords

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

{missRanger}

Overview

Installation

From CRAN

Development version

Usage

Sepal.Length Sepal.Width Petal.Length Petal.Width Species

5.1 3.5 1.4 0.2 setosa

4.9 3.0 1.4 NA setosa

4.7 3.2 1.3 0.2 setosa

4.6 3.1 1.5 0.2

NA 3.6 1.4 0.2 setosa

5.4 3.9 1.7 0.4

Sepal.Length Sepal.Width Petal.Length Petal.Width Species

1 5.1 3.5 1.4 0.2 setosa

2 4.9 3.0 1.4 0.2 setosa

3 4.7 3.2 1.3 0.2 setosa

4 4.6 3.1 1.5 0.2 setosa

5 5.2 3.6 1.4 0.2 setosa

6 5.4 3.9 1.7 0.4 setosa

How it works

References

Owner

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

cran.r-project.org: missRanger

Rankings

Maintainers (1)

Dependencies