Search Results for "python software foundation license"

statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all...

NAVAL-SEM is a fully offline desktop application for PLS-SEM and CB-SEM research. Designed for researchers, PhD scholars, professors, and analysts, NAVAL-SEM provides visual model building, bootstrapping, HTMT, fit indices, mediation analysis, MGA, and export support without requiring cloud access or subscriptions. Key features include: • PLS-SEM and covariance-based SEM • Visual drag-and-drop model builder • Bootstrapping and mediation analysis • HTMT, AVE, CR, Cronbach’s Alpha •...

That project aims at providing a clean API and a simple implementation, as a C++ library, of a Travel-oriented Distribution System. It corresponds to the simulated version of the real-world Computerized Reservation Systems (CRS).

That project aims at providing a clean API and a simple implementation, as a C++ library, of an Airline-related Inventory Management system. That library uses the Standard Airline IT C++ object model (http://sf.net/projects/stdair).

Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide...

Implementation in Python of some of the statistical methods provided by "asurv", the survival analysis software.

mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3.

This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.

This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.

Python module to track the overall median of a stream of values "on-line" in reasonably efficient fashion.