statsmodels.org
0.5 Release — statsmodels 0.6.1 documentation
http://www.statsmodels.org/stable/release/version0.5.html
What’s new in Statsmodels. Release 0.5.0. Statsmodels 0.5 is a large and very exciting release that brings together a year of work done by 38 authors, including over 2000 commits. It contains many new features and a large amount of bug fixes detailed below. See the list of fixed issues. For specific closed issues. The following major new features appear in this version. Support for Model Formulas via Patsy. Statsmodels now supports fitting models with a formula. This functionality is provided by patsy.
pfaffikus.de
Pfaffikus
http://www.pfaffikus.de/cccp.html
This package contains routines for solving convex optimization problems with cone constraints by means of interior-point methods. The implemented algorithms have been partially ported from the Python-module of cvxopt, which has been released under GPL 3 or newer (see cvxopt. For more information and references see the package's documentation and the file. Contained in the package). The current documentation can be downloaded as pdf-file here. The package is hosted on CRAN.
cvxpy.org
Install Guide — CVXPY 0.4.3 documentation
http://www.cvxpy.org/en/latest/install/index.html
To update CVXPY, first update NumPy and SciPy separately. Then run. Can cause errors, especially if you’re using Anaconda. The following instructions assume you already have Python installed. CVXPY supports both Python 2 and Python 3. We recommend using Anaconda. Rather than the Python that comes with the Mac and installing pip, nose, NumPy, SciPy, and CVXOPT through Anaconda. But it is not necessary to have Anaconda. To install CVXPY, and the instructions below assume you do not have Anaconda. There are...
jpktd.blogspot.com
joepy: Statsmodels Release 0.5.0rc1
http://jpktd.blogspot.com/2013/08/statsmodels-release-050rc1.html
Tuesday, August 6, 2013. Statsmodels Release 0.5.0rc1. After approximately a year since our last release, we are finally ready again for a new release of statsmodels. Skipper pushed the distribution files to pypi. During last year we merged many additional new features, and continued to improve our traditional models,. For now, I just copied, and lightly edited, some of the release information from the documentation. Statsmodels 0.5 is a large and very exciting release that brings together a year of ...
advanceddataanalytics.net
R Packages | Data Analytics & R
https://advanceddataanalytics.net/r-packages
What is …. Data Analytics and R. R Packages = 2665. Accurate, Adaptable, and Accessible Error Metrics for Predictive Models. Supplies tools for tabulating and analyzing the results of predictive models. The methods employed are applicable to virtually any predictive model and make comparisons between different methodologies straightforward. Tools for Approximate Bayesian Computation (ABC). Data Only: Tools for Approximate Bayesian Computation (ABC). Approximate Bayesian Computation via Random Forests.
hi.nextflu.org
nextflu / methods
http://hi.nextflu.org/methods
Real-time tracking of seasonal influenza. Virus evolution in humans. All source code is publicly available. And the exact steps of the nextflu algorithms are detailed in the processing pipeline files: H3N2 process.py. And Yam process.py. Here we give an overview of these methods. Broadly, nextflu. Contains two separate functions, the augur. Pipeline that processes FASTA sequence data and compiles JSON files, and auspice. Visualization package that displays these results in the browser. Sun et al, 2013.
charlesmartin14.wordpress.com
Advances in Convex NMF: Linear Programming | Machine Learning
https://charlesmartin14.wordpress.com/2013/05/06/advances-in-convex-nmf-part-1-linear-programming
Notes, thoughts, and practice of applied machine learning. Advances in Convex NMF: Linear Programming. Advances in Convex NMF: Linear Programming. May 6, 2013. March 24, 2014. Charles H Martin, PhD. Today I am going to look at a very important advance in one of my favorite Machine Learning algorithms, NMF (Non-Negative Matrix Factorization). Several approaches exist to improve traditional NMF [1], such as sparse NMF. Jordan et. al. [5]. In fact, it has been known for some time that CNMF could be re-formu...
relopezbriega.github.io
Algebra Lineal con Python
http://relopezbriega.github.io/blog/2015/06/14/algebra-lineal-con-python
Raul E. Lopez Briega. Matemáticas, análisis de datos y python. Algebra Lineal con Python. Sun 14 June 2015. Introducción ¶. Una de las herramientas matemáticas más utilizadas en machine learning. Es el Álgebra lineal. Por tanto, si queremos incursionar en el fascinante mundo del aprendizaje automático y el análisis de datos es importante reforzar los conceptos que forman parte de sus cimientos. Es una rama de las matemáticas. Comenzamos a trabajar con matrices. El estudio del Álgebra lineal. Es un vector...
