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SVR

Support Vector Regression using libSVM

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SVR

SVR SVR SVR Build Status Coverage Status

Support Vector Regression (SVR) analysis in Julia utilizing the libSVM library.

SVR is a module of MADS (Model Analysis & Decision Support).

Installation

Pkg.add("SVR")

Example

import SVR

# read a libSVM input file
x, y = SVR.readlibsvmfile("mg.libsvm")

# train a libSVM model
pmodel = SVR.train(y, x');

# predict based on the libSVM model
y_pr = SVR.predict(pmodel, x');

# save the libSVM model
SVR.savemodel(pmodel, "mg.model")

# free the memory allocation of the libSVM model
SVR.freemodel(pmodel)

MADS

MADS (Model Analysis & Decision Support) is an integrated open-source high-performance computational (HPC) framework in Julia. MADS can execute a wide range of data- and model-based analyses:

  • Sensitivity Analysis
  • Parameter Estimation
  • Model Inversion and Calibration
  • Uncertainty Quantification
  • Model Selection and Model Averaging
  • Model Reduction and Surrogate Modeling
  • Machine Learning and Blind Source Separation
  • Decision Analysis and Support

MADS has been tested to perform HPC simulations on a wide-range multi-processor clusters and parallel environments (Moab, Slurm, etc.). MADS utilizes adaptive rules and techniques which allows the analyses to be performed with a minimum user input. The code provides a series of alternative algorithms to execute each type of data- and model-based analyses.

Documentation

All the available MADS modules and functions are described at madsjulia.github.io

Installation

After starting Julia, execute:

Pkg.add("Mads")

Installation of MADS behind a firewall

Julia uses git for package management. Add in the .gitconfig file in your home directory:

[url "https://"]
        insteadOf = git://

or execute:

git config --global url."https://".insteadOf git://

Set proxies:

export ftp_proxy=http://proxyout.:8080
export rsync_proxy=http://proxyout.:8080
export http_proxy=http://proxyout.:8080
export https_proxy=http://proxyout.:8080
export no_proxy=.

For example, if you are doing this at LANL, you will need to execute the following lines in your bash command-line environment:

export ftp_proxy=http://proxyout.lanl.gov:8080
export rsync_proxy=http://proxyout.lanl.gov:8080
export http_proxy=http://proxyout.lanl.gov:8080
export https_proxy=http://proxyout.lanl.gov:8080
export no_proxy=.lanl.gov

MADS examples

In Julia REPL, do the following commands:

import Mads

To explore getting-started instructions, execute:

Mads.help()

There are various examples located in the examples directory of the Mads repository.

For example, execute

include(Mads.madsdir * "/../examples/contamination/contamination.jl")

to perform various example analyses related to groundwater contaminant transport, or execute

include(Mads.madsdir * "/../examples/bigdt/bigdt.jl")

to perform Bayesian Information Gap Decision Theory (BIG-DT) analysis.

Developers

Publications, Presentations, Projects

First Commit

12/20/2016

Last Touched

3 months ago

Commits

84 commits

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Used By: