mlpy - Machine Learning Python

mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and the GNU Scientific Libraries.

mlpy provides a wide range of state-of-the-art machine learning methods for supervised and unsupervised problems and it is aimed at finding a reasonable compromise among modularity, maintainability, reproducibility, usability and efficiency. mlpy is multiplatform, it works with Python 2 and 3 and it is Open Source, distributed under the GNU General Public License version 3.

If you use mlpy, please cite:

D. Albanese, R. Visintainer, S. Merler, S. Riccadonna, G. Jurman, C. Furlanello. mlpy: Machine Learning Python, 2012. arXiv:1202.6548 [bib]


mlpy was used in the following applications.


Regression: Least Squares, Ridge Regression, Last Angle Regression, Elastic Net, Kernel Ridge Regression, Support Vector Machines (SVR), Partial Least Squares (PLS)

Classification: Linear Discriminant Analysis (LDA), Basic Perceptron, Elastic Net, Logistic Regression, (Kernel) Support Vector Machines (SVM), Diagonal Linear Discriminant Analysis (DLDA), Golub Classifier, Parzen-based, (kernel) Fisher Discriminant Classifier k-Nearest-Neighbor, Iterative RELIEF, Classification Tree, Maximum Likelihood Classifier

Clustering: Hierarchical Clustering, Memory-saving Hierarchical Clustering, k-means

Dimensionality Reduction: (Kernel) Fisher Discriminant (FDA), Spectral Regression Discriminant Analysis (SRDA), (kernel) Principal Component Analysis (PCA)

Wavelet Submodule (mlpy.wavelet): Discrete, Undecimated and Continuous Wavelet Transform

Misc: Feature ranking/selection algorithms, Canberra stability indicator, resampling algorithms, error evaluation, peak finding algorithms, Dynamic Time Warping (DTW) distance, Longest Common Subsequence (LCS).

mlpy is completely compatible with PyInstaller


The latest release of mlpy is 3.5.0 (released 2012-03-12). You can download it as a source or as Windows installers (Download). mlpy is also available from the PyPi package repository. You can retrieve the latest code with the command (Mercurial is required):

hg clone mlpy-code

If you want to contribute to mlpy send an e-mail to: albanese AT


If you still have questions, feel free to send an email to the mlpy-general mailing list. To post a message to all the list members, send email to mlpy-general AT

Old Documentation:


Lead Developer: Davide Albanese (albanese AT

Contributors: Giuseppe Jurman, Stefano Merler, Roberto Visintainer, Marco Chierici, Lance Hepler.

Financial Contributions

FBK logo AIRC logo mlpy is a project of Predictive Models for Biological Predictive Models for Biological and Environmental Data Analysis (MPBA) Research Unit at Fondazione Bruno Kessler and it is co-funded by Associazione Italiana per la Ricerca sul Cancro

Last update: 29 February 2012
by Davide Albanese.

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