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The :mod:`parsimony.functions.objectives.functions` module contains ready-made common combinations of loss functions and penalties that can be used right away to analyse real data.
Created on Mon Apr 22 10:54:29 2013
Copyright (c) 2013-2014, CEA/DSV/I2BM/Neurospin. All rights reserved.
Author: Tommy Löfstedt, Vincent Guillemot, Edouard Duchesnay and Fouad Hadj-Selem
License: BSD 3-clause.
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CombinedFunction Combines one or more loss functions, any number of penalties and zero or one proximal operator. |
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LinearRegressionL1L2TV Combination (sum) of LinearRegression, L1, L2 and TotalVariation. |
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LinearRegressionL1L2GL Combination (sum) of RidgeRegression, L1 and Overlapping Group Lasso. |
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LogisticRegressionL1L2TV Combination (sum) of RidgeLogisticRegression, L1 and TotalVariation. |
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LogisticRegressionL1L2GL Combination (sum) of RidgeLogisticRegression, L1 and TotalVariation. |
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LinearRegressionL2SmoothedL1TV Combination (sum) of Linear Regression, L2 and simultaneously smoothed L1 and TotalVariation. |
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AugmentedLinearRegressionL1L2TV Combination (sum) of LinearRegression, L1, L2 and 1D TotalVariation with a linear constraint. |
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PrincipalComponentAnalysisL1TV Combination (sum) of PCA (Variance), L1 and TotalVariation |
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__package__ = |
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