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Package: science-machine-learning (1.7ubuntu3)

Debian Science Machine Learning packages

This metapackage will install packages useful for machine learning. Included packages range from knowledge-based (expert) inference systems to software implementing the advanced statistical methods that currently dominate the field.

Other Packages Related to science-machine-learning

  • depends
  • recommends
  • suggests
  • dep: science-config (= 1.7ubuntu3)
    Debian Science Project config package
  • dep: science-tasks (= 1.7ubuntu3)
    Debian Science tasks for tasksel
  • rec: autoclass
    automatic classification or clustering
  • rec: caffe-cpu
    Fast, open framework for Deep Learning (Meta)
  • rec: gprolog
    GNU Prolog compiler
  • rec: libcv-dev
    Package not available
  • rec: libevocosm-dev
    Package not available
  • rec: libfann-dev
    Development libraries and header files for FANN
  • rec: libga-dev
    C++ Library of Genetic Algorithm Components
  • rec: liblinear-dev
    Development libraries and header files for LIBLINEAR
  • rec: libmlpack-dev
    intuitive, fast, scalable C++ machine learning library (development libs)
  • rec: libocas-dev
    Development libraries and header files for LIBOCAS
  • rec: libshark-dev
    development files for Shark
  • rec: libsvm-dev
    LIBSVM header files
  • rec: libtorch3-dev
    State of the art machine learning library - development files
  • rec: libvigraimpex-dev
    development files for the C++ computer vision library
  • rec: mcl
    Markov Cluster algorithm
  • rec: octave-ga
    genetic optimization code for Octave
  • rec: python-genetic
    genetic algorithms in Python
  • rec: python-mdp
    Modular toolkit for Data Processing
  • rec: python-mvpa2
    multivariate pattern analysis with Python v. 2
  • rec: python-opencv
    Python bindings for the computer vision library
  • rec: python-pebl
    Python Environment for Bayesian Learning
  • rec: python-pyevolve
    complete genetic algorithm framework
  • rec: python-scikits-learn
    transitional compatibility package for scikits.learn -> sklearn migration
  • rec: python-statsmodels
    Python module for the estimation of statistical models
  • rec: python-vigra
    Python bindings for the C++ computer vision library
  • rec: r-cran-amore
    GNU R: A MORE flexible neural network package
  • rec: r-cran-bayesm
    GNU R package for Bayesian inference
  • rec: r-cran-class
    GNU R package for classification
  • rec: r-cran-cluster
    GNU R package for cluster analysis by Rousseeuw et al
  • rec: r-cran-gbm
    GNU R package providing Generalized Boosted Regression Models
  • rec: r-cran-mass
    GNU R package of Venables and Ripley's MASS
  • rec: r-cran-mcmcpack
    R routines for Markov chain Monte Carlo model estimation
  • rec: r-cran-mlbench
    GNU R Machine Learning Benchmark Problems
  • rec: r-cran-mnp
    GNU R package for fitting multinomial probit (MNP) models
  • rec: r-cran-msm
    GNU R Multi-state Markov and hidden Markov models in continuous time
  • rec: r-cran-tgp
    GNU R package "tgp: Bayesian treed Gaussian process models"
  • rec: scilab-ann
    Scilab module for artificial neural networks
  • rec: weka
    Machine learning algorithms for data mining tasks
  • rec: yap
    High-performance Prolog System
  • sug: ask
    Adaptive Sampling Kit for big experimental spaces
  • sug: caffe-cuda
    Package not available
  • sug: flann
    Package not available
  • sug: libacovea-dev
    Package not available
  • sug: libcomplearn-dev
    Package not available
  • sug: libdlib-dev
    C++ toolkit for machine learning and computer vision - development
  • sug: libqsearch-dev
    Package not available
  • sug: libroot-math-mlp-dev
    Package not available
  • sug: libroot-montecarlo-vmc-dev
    Package not available
  • sug: libroot-tmva-dev
    Package not available
  • sug: libshogun-dev
    Large Scale Machine Learning Toolbox
  • sug: lua-torch5
    Package not available
  • sug: lush
    Package not available
  • sug: pgapack
    Package not available
  • sug: pybrain
    Package not available
  • sug: python-mlpy
    high-performance Python package for predictive modeling
  • sug: python-orange
    Package not available
  • sug: python-pymc
    Package not available
  • sug: root-system
    Package not available
  • sug: science-numericalcomputation
    Debian Science Numerical Computation packages
  • sug: science-statistics
    Debian Science Statistics packages
  • sug: science-typesetting
    Debian Science typesetting packages
  • sug: torch-core-free
    Package not available
  • sug: toulbar2
    Exact combinatorial optimization for Graphical Models
  • sug: vowpal-wabbit
    fast and scalable online machine learning algorithm

Download science-machine-learning

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Architecture Package Size Installed Size Files
all 4.2 kB37 kB [list of files]