mlpy.sourceforge.netmlpy - Machine Learning Python

Download Documentation mlpy at SF minepy project News mlpy 3.5.0 released (2012-03-12). mlpy 3.4.0 released (2012-01-09). mlpy 3.3.0 released (2011-12-19). From this version, mlpy for Windows is compiled with Visual Studio Express 2008 in order to avoid runtime errors. mlpy 3.2.1 released (2011-12-9). From this version mlpy is available both for Python =2.6 and Python 3.X . mlpy 3.2 released (2011-12-5) mlpy 3.1 released (2011-12-1) 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 . Features 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 Download 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 http://hg.code.sf.net/p/mlpy/code mlpy-code If you want to contribute to mlpy send an e-mail to: albanese AT fbk.eu . Documentation Online Documentation PDF Documentation Wiki 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 googlegroups.com . Old Documentation: mlpy 3.4 mlpy 3.3 mlpy 3.2 mlpy 3.1 mlpy 3.0 People Lead Developer: Davide Albanese (albanese AT fbk.eu) Contributors: Giuseppe Jurman, Stefano Merler, Roberto Visintainer, Marco Chierici, Lance Hepler. Financial Contributions 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...