Mercurial > repos > bgruening > sklearn_sample_generator
changeset 22:25fce0cac6cf draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit cfc9fe24b7975fc5838bb3e456646202898eb977
| author | bgruening |
|---|---|
| date | Sat, 04 Aug 2018 17:29:32 -0400 |
| parents | 6dab79b662a7 |
| children | ca68fc647165 |
| files | README.rst |
| diffstat | 1 files changed, 9 insertions(+), 13 deletions(-) [+] |
line wrap: on
line diff
--- a/README.rst Sat Aug 04 12:15:30 2018 -0400 +++ b/README.rst Sat Aug 04 17:29:32 2018 -0400 @@ -1,9 +1,9 @@ -*************** Galaxy wrapper for scikit-learn library -*************** +*************************************** Contents ======== + - `What is scikit-learn?`_ - `Scikit-learn main package groups`_ - `Tools offered by this wrapper`_ @@ -16,10 +16,10 @@ ____________________________ -.. _What is scikit-learn? +.. _What is scikit-learn?: What is scikit-learn? -=========================== +===================== Scikit-learn is an open-source machine learning library for the Python programming language. It offers various algorithms for performing supervised and unsupervised learning as well as data preprocessing and transformation, model selection and evaluation, and dataset utilities. It is built upon SciPy (Scientific Python) library. @@ -29,9 +29,8 @@ .. _Scikit-learn main package groups: -====== Scikit-learn main package groups -====== +================================ Scikit-learn provides the users with several main groups of related operations. These are: @@ -54,9 +53,8 @@ .. _Tools offered by this wrapper: -=================== Available tools in the current wrapper -=================== +====================================== The current release of the wrapper offers a subset of the packages from scikit-learn library. You can find: @@ -73,16 +71,15 @@ .. _Machine learning workflows: Machine learning workflows -=============== +========================== Machine learning is about processes. No matter what machine learning algorithm we use, we can apply typical workflows and dataflows to produce more robust models and better predictions. Here we discuss supervised and unsupervised learning workflows. .. _Supervised learning workflows: -=================== Supervised machine learning workflows -=================== +===================================== **What is supervised learning?** @@ -132,9 +129,8 @@ .. _Unsupervised learning workflows: -======================= Unsupervised machine learning workflows -======================= +======================================= **What is unsupervised learning?**