Optunity
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  • Installing Optunity
  • User Guide
  • Examples
    • Python
      • Basic: cross-validation
      • Basic: nested cross-validation
      • Basic: minimizing a simple function
      • Basic: Sobol sequences
      • Optimization response surface
      • OpenCV: optical character recognition
      • sklearn: automated learning method selection and tuning
      • sklearn: SVM classification
      • sklearn: SVM regression
      • OpenCV
      • Optimizing a simple 2D parabola
      • scikit-learn
      • Spark
      • Theano
    • MATLAB
      • LS-SVMlab
    • R
      • Optimizing a simple 2D parabola
      • Ridge Regression
      • SVM (e1071)
      • xgboost
  • Notebooks
  • Using Other Environments
  • Optunity API
Optunity
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  • Examples
  • Edit on GitHub

Examples¶

Here you can find a variety of examples to illustrate how Optunity can be used in tandem with other machine learning software. We have split the examples per language and library.

To contribute examples, please send us a pull request on Github.

Python¶

The following examples are available as IPython notebooks in the OPTUNITY/notebooks folder:

  • Basic: cross-validation
    • Standard cross-validation
    • Using strata and clusters
    • Aggregators
    • Cross-validation with scikit-learn
  • Basic: nested cross-validation
  • Basic: minimizing a simple function
  • Basic: Sobol sequences
  • Optimization response surface
  • OpenCV: optical character recognition
  • sklearn: automated learning method selection and tuning
  • sklearn: SVM classification
    • Tune SVC with RBF kernel
    • Tune SVC without deciding the kernel in advance
  • sklearn: SVM regression
    • Nested cross-validation
    • Determining the kernel family during tuning

Additional examples:

  • OpenCV
  • Optimizing a simple 2D parabola
  • scikit-learn
    • Support vector machine classification (SVC)
    • Support vector machine regression (SVR)
  • Spark
    • Logistic regression with Spark and MLlib
  • Theano
    • Logistic regression

MATLAB¶

  • LS-SVMlab
    • Least-squares SVM classification
    • Least-squares SVM regression

R¶

  • Optimizing a simple 2D parabola
  • Ridge Regression
  • SVM (e1071)
  • xgboost
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© Copyright 2014, Marc Claesen, Jaak Simm and Dusan Popovic. Revision 019182ca.

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