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python3-sklearn-contrib-lightning-0.3.0-1.lbn19.x86_64: .. * mode: rst *.. image:: https://travisci.org/scikitlearncontrib/lightning.svg?branchmaster :target: https://travisci.org/scikitlearncontrib/lightning.. image:: https://ci.appveyor.com/api/projects/status/mmm0llccmvn5iooq?svgtrue :target: https://ci.appveyor.com/project/fabianp/lightningbpc6r/branch /masterlightning lightning is a library for largescale linear classification, regression and ...

python3-sklearn-compiledtrees-1.2-1.lbn19.x86_64: In some use cases, predicting given a model is in the hot-path, so speeding up decision tree evaluation is very useful. An effective way of speeding up evaluation of decision trees can be to generate code representing the evaluation of the tree, compile that to optimized object code, and dynamically load that file via dlopen/dlsym or equivalent. See https://courses.cs.washington.edu/courses/cse501/10au/compile-machlearn.pdf for a detailed discussion, and http://tullo.ch/articles/decision-tree-evaluation/ for a more pedagogical explanation and more benchmarks in C++. This package implements compiled decision tree evaluation for the simple case of a single-output regression tree or ensemble.

python3-scipy-0.16.1-6.lbn19.x86_64: Scipy is open-source software for mathematics, science, and engineering. The core library is NumPy which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers.

python3-scikit-video-0.1.2-1.lbn19.noarch: Video Processing SciKitVideo processing algorithms for SciPy, including IO, quality metrics, filtering, etc.

python3-scikit-sparse-0.3-1.lbn19.x86_64: Sparse matrix tools.This is a home for sparse matrix code in Python that plays well with scipy.sparse, but that is somehow unsuitable for inclusion in scipy proper. Usually this will be because it is released under the GPL.So far we have a wrapper for the CHOLMOD library for sparse Cholesky decomposition. Further contributions are welcome!

python3-scikit-neuralnetwork-0.7-1.lbn19.noarch: :orphan: scikit-neuralnetwork ==================== Deep neural network implementation without the learning cliff! This library implements multi-layer perceptrons as a wrapper for the powerful ``Lasagne`` library that's compatible with ``scikit-learn`` for a more user-friendly and Pythonic interface. **NOTE**: This project is possible thanks to the `nucl.ai Conference <http://nucl.ai/>`_ on ...

python3-scikit-nano-0.3.21-1.lbn19.noarch: scikitnano *scikitnano* is a python toolkit for generating and analyzing nanostructure data.*scikitnano* can generate structure data (i.e., atomic coordinates) for the following classes of nanostructures: * Fullerenes * Graphene * *N*layer graphene * Bilayer graphene with more fine control over relative layer orientation, including relative rotation ...

python3-scikit-monaco-0.2.1-1.lbn19.x86_64: scikitmonaco scikitmonaco is a library for Monte Carlo integration in python. The core is written in Cython, with processlevel parallelism to squeeze the last bits of speed out of the python interpreter.A code snippet is worth a thousand words. Let's look at integrating sqrt(x**2 + y**2 + z**2) in the unit square:.. code:: python >>> from skmonaco import mcquad >>> from math import sqrt ...

python3-scikit-learn-0.17.1-5.lbn19.x86_64: Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts.

python3-scikit-kinematics-0.2.8-1.lbn19.noarch: scikitkinematics *scikitkinematics* primarily contains functions for working with 3D kinematics, e.g quaternions and rotation matrices. This includes utilities to read in data from the following IMUsensors: XSens xio YEICompatible with Python 2 and 3.Dependencies numpy, scipy, matplotlib, pandas, sympy, easyguiHomepagehttp://work.thaslwanter.at/skinematics/html/Author: Thomas ...

python3-scikit-image-0.12.3-1.lbn19.x86_64: The scikit-image SciKit (toolkit for SciPy) extends scipy.ndimage to provide a versatile set of image processing routines.

python3-scikit-gpuppy-0.9.3-1.lbn19.x86_64: https://github.com/snphbaum/scikitgpuppyThis package provides means for modeling functions and simulations using Gaussian processes (aka Kriging, Gaussian random fields, Gaussian random functions). Additionally, uncertainty can be propagated through the Gaussian processes... note:: The Gaussian process regression and uncertainty propagation are based on Girard's thesis []_. ...

python3-scikit-fuzzy-0.2-1.lbn19.noarch: scikitfuzzy (a.k.a. skfuzzy): Fuzzy logic toolbox for Python.This package implements many useful tools for projects involving fuzzy logic, also known as grey logic.

python3-scikit-fmm-0.0.8-1.lbn19.x86_64: scikitfmm is a Python extension module which implements the fast marching method. Signed distance functions Travel time transforms (solutions to the Eikonal equation) Extension velocitieshttps://github.com/scikitfmm/scikitfmm

python3-scikit-chem-0.0.4-1.lbn19.noarch: [![DOI](https://zenodo.org/badge/4513/richlewis42/scikitchem.svg?style flatsquare)](http://dx.doi.org/10.5281/zenodo.15919) [![Coveralls](htt ps://img.shields.io/coveralls/richlewis42/scikitchem.svg?styleflatsqua re)](https://coveralls.io/r/richlewis42/scikitchem) ...

python3-scikit-build-0.2.0-1.lbn19.noarch: scikitbuild .. image:: https://img.shields.io/pypi/v/scikitbuild.svg?maxAge2592000 :target: https://pypi.python.org/pypi/scikitbuild.. image:: https://img.shields.io/pypi/dm/scikitbuild.svg?maxAge2592000 :target: https://pypi.python.org/pypi/scikitbuild.. image:: https://re quires.io/github/scikitbuild/scikitbuild/requirements.svg?branchmaster :target: ...

python3-scikit-MDR-0.1-1.lbn19.noarch: A sklearncompatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.Contact If you have any questions or comments about scikitMDR, please feel free to contact me via:Email: rso@randalolson.comor Twitter: https://twitter.com/randal_olsonThis project is hosted at https://github.com/rhiever/scikitmdr

python3-rpy2-2.8.3-1.lbn19.x86_64: Python interface to the R language (embedded R)


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