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.
Class Description IterativeReweightedLeastSquaresIterative Reweighted Least Squares for Logistic Regression fitting.
IterativeReweightedLeastSquaresTModelIterative Reweighted Least Squares for fitting Generalized Linear Models.
LogisticGradientDescentStochastic Gradient Descent learning for Logistic Regression fitting.
LowerBoundNewtonRaphsonLower-Bound Newton-Raphson for Multinomial logistic regression fitting.
MultinomialLogisticLearningTMethodGradient optimization for Multinomial logistic regression fitting.
NonlinearLeastSquaresNon-linear Least Squares for
NonlinearRegressionoptimization.
NonNegativeLeastSquaresNon-negative Least Squares for
MultipleLinearRegressionoptimization.
ProportionalHazardsNewtonRaphsonNewton-Raphson learning updates for Cox's Proportional Hazards models.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4