{"repo":"FenTechSolutions/CausalDiscoveryToolbox","free":true,"listed":false,"github":"https://github.com/FenTechSolutions/CausalDiscoveryToolbox","clone":"git clone https://github.com/FenTechSolutions/CausalDiscoveryToolbox.git","description":"Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.","language":"Python","stars":1236,"topics":["causal-inference","graph","causality","causal-models","algorithm","machine-learning","graph-structure-recovery","python","causal-discovery","toolbox"],"license":"MIT","category":"machine-learning","readme_excerpt":"The Causal Discovery Toolbox is a package for causal inference in graphs and in the pairwise settings for Python =3.5. Tools for graph structure recovery and dependencies are included. The package is based on Numpy, Scikit-learn, Pytorch and R. It implements lots of algorithms for graph structure recovery (including algorithms from the bnlearn , pcalg packages), mainly based out of observational data. Check out the documentation here Please cite us if you use our software A tutorial is available here Install it using pip: (See more details on installation below) Docker images Docker images are available, including all the dependencies, and enabled functionalities: Branch master dev :----------------: :--------------------------------------------------------------------------------------------------------------------------------------: :------------------------------------------------------------------------------------------------------------------------------------: Python 3.6 - CPU Python 3.6 - GPU Installation The packages requires a python version =3.5, as well as some libraries listed in requirements file. For some additional functionalities, more libraries are needed for these extra functions and options to become available. Here is a quick install guide of the package, starting off with the minimal install up to the full installation. Note : A (mini/ana)conda framework would help installing all those packages and therefore could be recommended for non-expert users. Ins","default_branch":null,"files":null,"tree":[],"storefront":"/r/FenTechSolutions","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/FenTechSolutions/CausalDiscoveryToolbox/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}