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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
  ClassDescription
Public classCode exampleIterativeReweightedLeastSquares
Iterative Reweighted Least Squares for Logistic Regression fitting.
Public classIterativeReweightedLeastSquaresTModel
Iterative Reweighted Least Squares for fitting Generalized Linear Models.
Public classLogisticGradientDescent
Stochastic Gradient Descent learning for Logistic Regression fitting.
Public classCode exampleLowerBoundNewtonRaphson
Lower-Bound Newton-Raphson for Multinomial logistic regression fitting.
Public classMultinomialLogisticLearningTMethod
Gradient optimization for Multinomial logistic regression fitting.
Public classCode exampleNonlinearLeastSquares
Non-linear Least Squares for NonlinearRegression optimization.
Public classNonNegativeLeastSquares
Non-negative Least Squares for NonlinearRegression optimization.
Public classProportionalHazardsNewtonRaphson
Newton-Raphson learning updates for Cox's Proportional Hazards models.