ml Namespace Reference

Namespaces
	Clustering
	Methods and classes for clustering algorithms.
	Crossvalidation
	Methods used for cross-validation.
	DecisionTrees
	Helper functions and classes for decision trees.
	Features
	Utilities and types for working with features.
	Kernels
	Methods and classes for working with kernels.
	LinearAlgebra
	Linear algebra helper functions.
	LinearRegression
	Linear regression algorithms.
	Statistics
	Statistical functions.

Classes
class	AbstractLogisticRegression
	Abstract implementation, sharing the common parameters and stopping criterion. More...
class	BallTree
	Ball tree: an efficient tree structure for nearest-neighbour search in R^D space. More...
class	ConjugateGradientLogisticRegression
	Conjugate gradient logistic regression, as described in Sec. 4 of Thomas P. Minka, "A comparison of numerical optimizers for logistic regression". More...
class	DecisionTree
	Decision tree. More...
class	EM
	Gaussian Expectation-Maximisation algorithm. More...
class	LogisticRegression
	Binomial logistic regression algorithm. More...

Typedefs
typedef DecisionTree< double >	RegressionTree
	Decision tree for linear regression.
typedef DecisionTree< unsigned int >	ClassificationTree
	Decision tree for multinomial classification.

Detailed Description

(C) 2021 Roman Werpachowski