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Accord.Statistics.Models.Regression.Fitting Namespace |
Fitting (learning) algorithms for regression models, such as the Iterative Reweighted Least Squares for standard logistic regressors and the Lower-Bound approximator for multinomial logistic regression.
Classes| Class | Description | |
|---|---|---|
  | IterativeReweightedLeastSquares |
Iterative Reweighted Least Squares for Logistic Regression fitting.
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| IterativeReweightedLeastSquaresTModel |
Iterative Reweighted Least Squares for fitting Generalized Linear Models.
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| LogisticGradientDescent |
Stochastic Gradient Descent learning for Logistic Regression fitting.
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| LowerBoundNewtonRaphson |
Lower-Bound Newton-Raphson for Multinomial logistic regression fitting.
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| MultinomialLogisticLearningTMethod |
Gradient optimization for Multinomial logistic regression fitting.
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| NonlinearLeastSquares |
Non-linear Least Squares for NonlinearRegression optimization.
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| NonNegativeLeastSquares |
Non-negative Least Squares for MultipleLinearRegression optimization.
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| ProportionalHazardsNewtonRaphson |
Newton-Raphson learning updates for Cox's Proportional Hazards models.
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