mlpack 4

mlpack 4: a fast, header-only C++ machine learning library - Published in JOSS (2023)

Science Score: 95.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
✓
DOI references
Found 4 DOI reference(s) in README and JOSS metadata
○
Academic publication links
✓
Committers with academic emails
31 of 334 committers (9.3%) from academic institutions
○
Institutional organization owner
✓
JOSS paper metadata
Published in Journal of Open Source Software

Keywords

c-plus-plus deep-learning hacktoberfest machine-learning machine-learning-library nearest-neighbor-search regression scientific-computing

Keywords from Contributors

astronomy standardization meshing sun solar-physics solar astropy sunpy correlation fluxes

Last synced: 4 months ago · JSON representation

Repository

mlpack: a fast, header-only C++ machine learning library

Basic Info

Host: GitHub
Owner: mlpack
License: other
Language: C++
Default Branch: master
Homepage: https://www.mlpack.org/
Size: 263 MB

Statistics

Stars: 5,467
Watchers: 188
Forks: 1,666
Open Issues: 28
Releases: 52

Topics

c-plus-plus deep-learning hacktoberfest machine-learning machine-learning-library nearest-neighbor-search regression scientific-computing

Created about 11 years ago · Last pushed 4 months ago

Metadata Files

Readme Changelog Contributing Funding License Code of conduct Governance

a fast, header-only machine learning library

Home | Download | Documentation | Help |

Download: current stable version (4.6.2)

mlpack is an intuitive, fast, and flexible header-only C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers.

mlpack's lightweight C++ implementation makes it ideal for deployment, and it can also be used for interactive prototyping via C++ notebooks (these can be seen in action on mlpack's homepage).

In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings.

Quick links:

Quickstart guides: C++, CLI, Python, R, Julia, Go
mlpack homepage
mlpack documentation
Examples repository
Tutorials
Development Site (Github)

mlpack uses an open governance model and is fiscally sponsored by NumFOCUS. Consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

1. Citation details

If you use mlpack in your research or software, please cite mlpack using the citation below (given in BibTeX format):

@article{mlpack2023,
    title     = {mlpack 4: a fast, header-only C++ machine learning library},
    author    = {Ryan R. Curtin and Marcus Edel and Omar Shrit and 
                 Shubham Agrawal and Suryoday Basak and James J. Balamuta and 
                 Ryan Birmingham and Kartik Dutt and Dirk Eddelbuettel and 
                 Rishabh Garg and Shikhar Jaiswal and Aakash Kaushik and 
                 Sangyeon Kim and Anjishnu Mukherjee and Nanubala Gnana Sai and 
                 Nippun Sharma and Yashwant Singh Parihar and Roshan Swain and 
                 Conrad Sanderson},
    journal   = {Journal of Open Source Software},
    volume    = {8},
    number    = {82},
    pages     = {5026},
    year      = {2023},
    doi       = {10.21105/joss.05026},
    url       = {https://doi.org/10.21105/joss.05026}
}

Citations are beneficial for the growth and improvement of mlpack.

2. Dependencies

mlpack requires the following additional dependencies:

C++17 compiler
Armadillo >= 10.8
ensmallen >= 2.10.0
cereal >= 1.1.2

If the STB library headers are available, image loading support will be available.

If you are compiling Armadillo by hand, ensure that LAPACK and BLAS are enabled.

3. Installation

Detailed installation instructions can be found on the Installing mlpack page.

4. Usage from C++

Once headers are installed with make install, using mlpack in an application consists only of including it. So, your program should include mlpack:

```c++

include

```

and when you link, be sure to link against Armadillo. If your example program is my_program.cpp, your compiler is GCC, and you would like to compile with OpenMP support (recommended) and optimizations, compile like this:

sh g++ -O3 -std=c++17 -o my_program my_program.cpp -larmadillo -fopenmp

Note that if you want to serialize (save or load) neural networks, you should add #define MLPACK_ENABLE_ANN_SERIALIZATION before including <mlpack.hpp>. If you don't define MLPACK_ENABLE_ANN_SERIALIZATION and your code serializes a neural network, a compilation error will occur.

Warning: older versions of OpenBLAS (0.3.26 and older) compiled to use pthreads may use too many threads for computation, causing significant slowdown. OpenBLAS versions compiled with OpenMP do not suffer from this issue. See the test build guide for more details and simple workarounds.

4.1. Reducing compile time

mlpack is a template-heavy library, and if care is not used, compilation time of a project can be very high. Fortunately, there are a number of ways to reduce compilation time:

Include individual headers, like <mlpack/methods/decision_tree.hpp>, if you are only using one component, instead of <mlpack.hpp>. This reduces the amount of work the compiler has to do.
Only use the MLPACK_ENABLE_ANN_SERIALIZATION definition if you are serializing neural networks in your code. When this define is enabled, compilation time will increase significantly, as the compiler must generate code for every possible type of layer. (The large amount of extra compilation overhead is why this is not enabled by default.)
If you are using mlpack in multiple .cpp files, consider using extern templates so that the compiler only instantiates each template once; add an explicit template instantiation for each mlpack template type you want to use in a .cpp file, and then use extern definitions elsewhere to let the compiler know it exists in a different file.

Other strategies exist too, such as precompiled headers, compiler options, ccache, and others.

5. Building mlpack's test suite

See the installation instruction section.

6. Further Resources

More documentation is available for both users and developers.

Documentation homepage

To learn about the development goals of mlpack in the short- and medium-term future, see the vision document.

If you have problems, find a bug, or need help, you can try visiting the mlpack help page, or mlpack on Github. Alternately, mlpack help can be found on Matrix at #mlpack; see also the community page.

Owner

Name: mlpack
Login: mlpack
Kind: organization
Email: mlpack@lists.mlpack.org

Website: http://www.mlpack.org/
Repositories: 17
Profile: https://github.com/mlpack

a fast, header-only C++ machine learning library

JOSS Publication

mlpack 3: a fast, flexible machine learning library

Published

June 18, 2018

DOI

10.21105/joss.00726

Volume 3, Issue 26, Page 726

Authors

Ryan R. Curtin

Center for Advanced Machine Learning, Symantec Corporation

Marcus Edel

Institute of Computer Science, Free University of Berlin

Mikhail Lozhnikov

Moscow State University, Faculty of Mechanics and Mathematics

Yannis Mentekidis

None

Sumedh Ghaisas

None

Shangtong Zhang

University of Alberta

Editor

Kevin M. Moerman

Papers & Mentions

Total mentions: 3

Non-linear regression models for time to flowering in wild chickpea combine genetic and climatic factors

DOI: 10.1186/s12870-019-1685-2
OpenAlex ID: https://openalex.org/W2923714128
Published: March 2019

Last synced: 2 months ago

LinkPred: a high performance library for link prediction in complex networks

DOI: 10.7717/peerj-cs.521
OpenAlex ID: https://openalex.org/W3163156178
Published: May 2021

Last synced: 2 months ago

iMOKA: k-mer based software to analyze large collections of sequencing data

DOI: 10.1186/s13059-020-02165-2
OpenAlex ID: https://openalex.org/W3091943457
Published: October 2020

Last synced: 2 months ago

GitHub Events

Total

Create event: 6
Release event: 4
Issues event: 51
Watch event: 382
Delete event: 4
Issue comment event: 482
Push event: 105
Gollum event: 5
Pull request review comment event: 936
Pull request event: 245
Pull request review event: 854
Fork event: 99

Last Year

Create event: 6
Release event: 4
Issues event: 52
Watch event: 383
Delete event: 4
Issue comment event: 484
Push event: 105
Gollum event: 5
Pull request review comment event: 941
Pull request event: 245
Pull request review event: 862
Fork event: 99

Committers

Last synced: 5 months ago

All Time

Total Commits: 27,991
Total Committers: 334
Avg Commits per committer: 83.805
Development Distribution Score (DDS): 0.74

Past Year

Commits: 342
Committers: 20
Avg Commits per committer: 17.1
Development Distribution Score (DDS): 0.386

Top Committers

Name	Email	Commits
Ryan Curtin	r**n@r**g	7,275
(no author)	(**)@9**3	3,227
Dongryeol Lee	d**e@g**m	2,664
Omar Shrit	o**r@s**e	1,379
Marcus Edel	m**l@f**e	973
tekhnofiend	n**x@g**m	711
vasiloglou	n**l@i**m	476
jeffinsam	j**m@k**n	366
Garry Boyer	o**e@g**m	339
Bill March	m**h@i**u	335
Yashwant	y**h@g**m	321
Rishabh Garg	5****8	272
Roberto Hueso Gomez	r**6@g**m	258
Adam Kropp	3****p	238
shubham1206agra	t**4@i**n	206
stereomatchingkiss	s**s@g**m	202
Parikshit Ram	p**m@g**u	201
houyang	h**g@9**3	200
MarcosPividori	m**i@g**m	186
NippunSharma	i**n@g**m	179
gmravi2003	g**3@g**u	177
Wenhao-H	w**k@g**m	176
soyeon	s**n@9**3	172
kartikdutt18	k**t@l**n	165
nishantkr18	n**r@g**m	158
Manish	m**r@g**m	156
Mrityunjay Tripathi	m**8@g**m	155
Kirill Mishchenko	k**o@g**m	150
heisenbuug	d**x@g**m	135
rriegel	r**l@9**3	135
and 304 more...

Committer Domains (Top 20 + Academic)

itbhu.ac.in: 3 gatech.edu: 3 suiit.ac.in: 2 pop-os.localdomain: 2 qq.com: 2 sagesenses.com: 1 u.nus.edu: 1 pilani.bits-pilani.ac.in: 1 .com: 1 iitp.ac.in: 1 tutanota.com: 1 debian.org: 1 in.ibm.com: 1 students.uni-mainz.de: 1 pearlmutter.net: 1 lambertsen.one: 1 eglp.com: 1 assrc.us: 1 crfs.com: 1 ratml.org: 1 fu-berlin.de: 1 karunya.edu.in: 1 ices.utexas.edu: 1 iitd.ac.in: 1 iitkgp.ac.in: 1 ualberta.ca: 1 wmgds.wmg.warwick.ac.uk: 1 students.iitmandi.ac.in: 1 hyderabad.bits-pilani.ac.in: 1 dlr.de: 1 dyn148112.cc.lehigh.edu: 1 umail.iu.edu: 1 vitstudent.ac.in: 1 uiowa.edu: 1 dyn149223.cc.lehigh.edu: 1 ubuntu.ubuntu-domain: 1 st.niituniversity.in: 1 rit.edu: 1 uni-bonn.de: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 189
Total pull requests: 710
Average time to close issues: 8 months
Average time to close pull requests: about 1 month
Total issue authors: 111
Total pull request authors: 74
Average comments per issue: 5.58
Average comments per pull request: 2.47
Merged pull requests: 460
Bot issues: 0
Bot pull requests: 7

Past Year

Issues: 37
Pull requests: 299
Average time to close issues: 27 days
Average time to close pull requests: 13 days
Issue authors: 32
Pull request authors: 30
Average comments per issue: 3.49
Average comments per pull request: 1.92
Merged pull requests: 199
Bot issues: 0
Bot pull requests: 2

View more stats

Top Authors

Issue Authors

rcurtin (20)
yurivict (10)
shrit (8)
eddelbuettel (7)
coatless (6)
kiner-shah (6)
mrdaybird (5)
IgorWojas (4)
GLmontanari (3)
kumarutkarsh1248 (3)
cgiachalis (3)
shaojunjie0912 (3)
Adarsh97 (2)
Patschkowski (2)
akropp (2)

Pull Request Authors

rcurtin (297)
shrit (98)
TirelessClock (24)
eddelbuettel (23)
AdarshSantoria (21)
MarkFischinger (16)
kumarutkarsh1248 (13)
aadi-raj (13)
andrewfurey21 (12)
marlamb (12)
ViswanathBalla22 (11)
IWNMWE (11)
conradsnicta (10)
mrdaybird (7)
nzachary (7)

Top Labels

Issue Labels

t: bug report (71) s: stale (70) s: unanswered (39) c: methods (24) c: documentation (20) t: feature request (20) c: build system (13) t: question (12) good first issue (12) help wanted (12) s: unlabeled (11) c: core (10) c: binding (8) c: automatic bindings (8) t: added feature (6) s: keep open (6) c: testing (3) s: answered (3) update dependencies (3) i: installation (2) t: bug in other software (1) i: other software (1) s: fixed (1) s: spam (1) t: bugfix (1)

Pull Request Labels

t: bugfix (140) c: documentation (123) t: added feature (102) s: needs review (93) c: methods (92) s: stale (79) s: unlabeled (60) s: unanswered (59) c: build system (50) c: automatic bindings (30) c: core (30) c: testing (27) t: release (27) s: keep open (15) embedded systems (10) c: binding (9) update dependencies (7) automated PR (5) t: bug report (1) s: spam (1) Stale (1)

Packages

Total packages: 7
Total downloads:
- cran 1,229 last-month
- pypi 2,565 last-month
- nuget 9,528 total
Total docker downloads: 48

Total dependent packages: 10
(may contain duplicates)
Total dependent repositories: 16
(may contain duplicates)
Total versions: 76
Total maintainers: 4

pypi.org: mlpack

a flexible, fast machine learning library

Homepage: http://www.mlpack.org/
Documentation: http://www.mlpack.org/doc/mlpack-4.6.2/python.html
License: BSD
Latest release: 4.6.2
published 7 months ago

Versions: 25
Dependent Packages: 1
Dependent Repositories: 7
Downloads: 2,397 Last month

Rankings

Stargazers count: 1.0%

Forks count: 1.1%

Dependent packages count: 3.3%

Average: 3.4%

Dependent repos count: 5.7%

Downloads: 6.0%

Maintainers (2)

rcurtin mlpack-travis-worker

Last synced: 4 months ago

nuget.org: mlpack-windows.redist

Redistributable components for package 'mlpack-windows'. This package should only be installed as a dependency. (This is not the package you are looking for).

Homepage: https://github.com/mlpack/mlpack
License: other
Latest release: 2.2.0.1
published almost 126 years ago

Versions: 3
Dependent Packages: 1
Dependent Repositories: 0

Rankings

Forks count: 0.2%

Stargazers count: 0.3%

Average: 5.9%

Dependent packages count: 10.3%

Dependent repos count: 12.7%

Last synced: 4 months ago

pypi.org: mlpack3

a flexible, fast machine learning library

Homepage: http://www.mlpack.org/
Documentation: http://www.mlpack.org/docs/mlpack-3.4.2/python.html
License: BSD
Latest release: 3.4.2
published about 5 years ago

Versions: 14
Dependent Packages: 0
Dependent Repositories: 3
Downloads: 168 Last month

Rankings

Stargazers count: 1.0%

Forks count: 1.1%

Average: 7.3%

Dependent packages count: 7.4%

Dependent repos count: 9.2%

Downloads: 18.1%

Maintainers (2)

rcurtin mlpack-travis-worker

Last synced: 4 months ago

cran.r-project.org: mlpack

'Rcpp' Integration for the 'mlpack' Library

Homepage: https://www.mlpack.org/doc/user/bindings/r.html
Documentation: http://cran.r-project.org/web/packages/mlpack/mlpack.pdf
License: BSD_3_clause + file LICENSE
Latest release: 4.6.3
published 4 months ago

Versions: 16
Dependent Packages: 7
Dependent Repositories: 4
Downloads: 1,229 Last month
Docker Downloads: 48

Rankings

Stargazers count: 0.0%

Forks count: 0.0%

Dependent packages count: 7.1%

Average: 7.9%

Dependent repos count: 14.8%

Downloads: 17.6%

Maintainers (1)

ryan@ratml.org

Last synced: 4 months ago

nuget.org: mlpack-windows

mlpack is an intuitive, fast, scalable C++ machine learning library, meant to be a machine learning analog to LAPACK. It aims to implement a wide array of machine learning methods and functions as a swiss army knife for machine learning researchers.

Homepage: https://github.com/mlpack/mlpack
License: other
Latest release: 2.2.0
published over 8 years ago

Versions: 6
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 9,528 Total

Rankings

Forks count: 0.2%

Stargazers count: 0.4%

Dependent repos count: 7.0%

Average: 9.4%

Downloads: 18.7%

Dependent packages count: 20.7%

Maintainers (1)

NaxAlpha

Last synced: 4 months ago

conda-forge.org: mlpack

mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs and Python bindings.

Homepage: http://www.mlpack.org
License: BSD-3-Clause
Latest release: 4.0.0
published about 3 years ago

Versions: 9
Dependent Packages: 0
Dependent Repositories: 1

Rankings

Forks count: 3.9%

Stargazers count: 5.3%

Average: 21.2%

Dependent repos count: 24.1%

Dependent packages count: 51.5%

Last synced: 4 months ago

conda-forge.org: r-mlpack

Homepage: https://www.mlpack.org/doc/mlpack-git/r_documentation.html
License: BSD-3-Clause
Latest release: 4.0.0
published about 3 years ago

Versions: 3
Dependent Packages: 1
Dependent Repositories: 0

Rankings

Dependent packages count: 28.8%

Average: 31.4%

Dependent repos count: 34.0%

Last synced: 4 months ago

Dependencies

src/mlpack/bindings/go/mlpack/go.mod go

gonum.org/v1/gonum v0.7.0

src/mlpack/bindings/go/mlpack/go.sum go

github.com/ajstarks/svgo v0.0.0-20180226025133-644b8db467af
github.com/fogleman/gg v1.2.1-0.20190220221249-0403632d5b90
github.com/golang/freetype v0.0.0-20170609003504-e2365dfdc4a0
github.com/jung-kurt/gofpdf v1.0.3-0.20190309125859-24315acbbda5
golang.org/x/exp v0.0.0-20180321215751-8460e604b9de
golang.org/x/exp v0.0.0-20180807140117-3d87b88a115f
golang.org/x/exp v0.0.0-20190125153040-c74c464bbbf2
golang.org/x/image v0.0.0-20180708004352-c73c2afc3b81
golang.org/x/tools v0.0.0-20180525024113-a5b4c53f6e8b
golang.org/x/tools v0.0.0-20190206041539-40960b6deb8e
gonum.org/v1/gonum v0.0.0-20180816165407-929014505bf4
gonum.org/v1/gonum v0.7.0
gonum.org/v1/netlib v0.0.0-20190313105609-8cb42192e0e0
gonum.org/v1/plot v0.0.0-20190515093506-e2840ee46a6b
rsc.io/pdf v0.1.1

.github/workflows/main.yml actions

actions/cache v3 composite
actions/cache v1 composite
actions/checkout v3 composite
actions/download-artifact v2 composite
actions/upload-artifact v3 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite

.github/workflows/update-catch.yaml actions

actions/checkout v2 composite
peter-evans/create-pull-request v3 composite

.github/workflows/update-cli11.yaml actions

actions/checkout v2 composite
peter-evans/create-pull-request v3 composite

mlpack 4

Science Score: 95.0%

Keywords

Keywords from Contributors

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

a fast, header-only machine learning library

Home | Download | Documentation | Help |

0. Contents

1. Citation details

2. Dependencies

3. Installation

4. Usage from C++

include

4.1. Reducing compile time

5. Building mlpack's test suite

6. Further Resources

Owner

JOSS Publication

mlpack 3: a fast, flexible machine learning library

Authors

Editor

Tags

Papers & Mentions

Non-linear regression models for time to flowering in wild chickpea combine genetic and climatic factors

LinkPred: a high performance library for link prediction in complex networks

iMOKA: k-mer based software to analyze large collections of sequencing data

GitHub Events

Total

Last Year

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Past Year

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Packages

pypi.org: mlpack

Rankings

Maintainers (2)

nuget.org: mlpack-windows.redist

Rankings

pypi.org: mlpack3

Rankings

Maintainers (2)

cran.r-project.org: mlpack

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Maintainers (1)

nuget.org: mlpack-windows

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conda-forge.org: mlpack

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conda-forge.org: r-mlpack

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Dependencies