MLPACK (C++ library)
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| MLPACK | |
|---|---|
| Type | Private |
| Industry | Machine Learning |
| Founded | 2011 |
| Headquarters | Atlanta, Georgia |
| Key people | [1] |
| Investors | Fast Track at Georgia Tech. |
| Related Certifications | Certificate in Machine Learning Industry Overview |
mlpack is a C++ Machine Learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users. This is done by providing a set of command-line executables which can be used as black boxes, and a modular C++ API for expert users and researchers to easily make changes to the internals of the algorithms.[2]
mlpack is supported by Georgia Institute of Technology and contributions from around the world. around the world. It is released free of charge, under the 3-clause BSD License (more information). (Versions older than 1.0.12 were released under the GNU Lesser General Public License: LGPL, version 3.)
Contents
History
- Originally, mlpack was produced by the FASTLab[3] at Georgia Tech[4]
- mlpack was originally presented at the BigLearning workshop of NIPS 2011[5] and later published in the Journal of Machine Learning Research[6].
- Dec 17, 2011, mlpack 1.0.0 was released.[7]
- july 21st, 2016, mlpack 2.0.3 was released.[8]
Supported Algorithms
- Collaborative Filtering
- Density Estimation Trees
- Euclidean Minimum Spanning Trees
- Fast Exact Max-Kernel Search (FastMKS)
- Gaussian Mixture Models (GMMs)
- Hidden Markov Models (HMMs)Gaussian Mixture Models (GMMs)
- Kernel Principal Component Analysis (KPCA)
- K-Means Clustering
- Least-Angle Regression (LARS/LASSO)
- Local Coordinate Coding
- Locality-Sensitive Hashing (LSH)
- Logistic regression
- Naive Bayes Classifier
- Neighbourhood Components Analysis (NCA)
- Non-negative Matrix Factorization (NMF)
- Principal Components Analysis (PCA)
- Independent component analysis (ICA)
- Rank-Approximate Nearest Neighbor (RANN)
- Simple Least-Squares Linear Regression (and Ridge Regression)
- Sparse Coding
- Tree-based Neighbor Search (all-k-nearest-neighbors, all-k-furthest-neighbors), using either kd-trees or cover trees
- Tree-based Range Search
Top 5 Recent Tweets
| Date | Author | Comment |
|---|---|---|
| February 06, 2023 | MLRepositories | mlpack: mlpack: a fast, header-only C++ machine learning library
Lang: C++ ⭐️ 4235
|
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- ↑ https://github.com/mlpack/mlpack/graphs/contributors
- ↑ http://mlpack.org/about.html
- ↑ http://www.fast-lab.org/
- ↑ http://gatech.edu/
- ↑ http://mlpack.org/mlpack_biglearn.pdf
- ↑ http://mlpack.org/mlpack_jmlr.pdf
- ↑ http://www.mlpack.org/trac/query?status=closed&milestone=mlpack+1.0.0
- ↑ http://mlpack.org/history.html
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