mlpy is a high-performance Python package for predictive modeling. It makes extensive use of NumPy (http://scipy.org) to provide fast N-dimensional array manipulation and easy integration of C code. mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. The package includes tools to measure stability in sets of ranked feature lists.
mlpy is a high-performance Python package for predictive modeling. It makes extensive use of NumPy (http://scipy.org) to provide fast N-dimensional array manipulation and easy integration of C code. mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. The package includes tools to measure stability in sets of ranked feature lists.
To install py27-mlpy, run the following command in macOS terminal (Applications->Utilities->Terminal)
sudo port install py27-mlpy
To see what files were installed by py27-mlpy, run:
port contents py27-mlpy
To later upgrade py27-mlpy, run:
sudo port selfupdate && sudo port upgrade py27-mlpy
Reporting an issue on MacPorts Trac
The MacPorts Project uses a system called Trac to file tickets to report bugs and enhancement requests.
Though anyone may search Trac for tickets, you must have a GitHub account in order to login to Trac to create tickets.