LEMGA Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

_boost_cg
_boost_gd
_conjugate_gradient
_gd_adaptive
_gd_momentum	Gradient descent with momentum
_gd_weightdecay	Gradient descent with weight decay
_gradient_descent	Gradient descent
_line_search
_mgn_gd
_register_creator
_search	Interface used in iterative optimization algorithms
_shared_ptr
AdaBoost	AdaBoost (adaptive boosting)
AdaBoost_ECOC	AdaBoost.ECC with exponential cost and Hamming distance
AdaCost
Aggregating	An abstract class for aggregating
Bagging	Bagging (boostrap aggregating)
bisigmoid
Boosting	Boosting generates a linear combination of hypotheses
Boosting::BoostWgt	Weight in gradient descent
Cascade	Aggregate hypotheses in a cascade (sequential) way
CGBoost	CGBoost (Conjugate Gradient Boosting)
const_shared_ptr	Shared pointers (whose content can not be changed)
DataFeeder	Feed (random splitted) training and testing data
DataFeeder::LINEAR_SCALE_PARAM
dataset	Class template for storing, retrieving, and manipulating a vector of input-output style data
exponential
FeedForwardNN
Kernel	The operator() gives the inner-product in the transformed space
LearnModel	A unified interface for learning models
Linear
logistic
LPBoost	LPBoost (Linear-Programming Boosting)
MgnBoost	MgnBoost (margin maximizing boosting)
MgnCost	Cost proxy used in MgnBoost
MultiClass_ECOC	Multiclass classification using error-correcting output code
NNLayer	A layer in a neural network
Object	The root (ancestor) of all classes
Perceptron	Perceptron models a type of artificial neural network that consists of only one neuron, invented by Frank Rosenblatt in 1957
Perceptron
Polynomial
Pulse	Multi-transition pulse functions (step functions)
RBF
sigmoid
Sigmoid
Stump
Stump	Decision stump
SVM
var_shared_ptr	Shared pointers (whose content can be changed)

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