List

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

[detail level 123]

benchmark
dataset
DataSet
DataStream
evaluation
layer
Layer
SigmaPiLayer
metalearning
AdaBoost
Bagging
net
Learner
Activation
Error
Net
RBM
SparseAutoEncoder
openann
OpenANN
FANN
LibSVM
AdaBoost	Adaptive Boosting
Bagging	Bootstrap Aggregating
CompressionMatrixFactory	Creates several types of matrices for compression
Compressor	Compresses arbitrary one-dimensional data
EnsembleLearner
Evaluator	Evaluates a Learner
MulticlassEvaluator	Evaluates learners for multiclass problems
IntrinsicPlasticity	Learns the parameters of a logistic sigmoid activation function
DataSet	Data set interface
DataSetView	An index-based dataset wrapper for representing efficient dataset views on any DataSet instance
DataStream	Streams training data for online training
DirectStorageDataSet	Stores the inputs and outputs of the data set directly in two matrices
FloatingPointFormatter	Wraps a value and its precision for logging
Log	Global logger
Logger	A local logger that can redirect messages to several targets
WeightedDataSet	Resampled dataset based on the original dataset
KMeans	K-means clustering
AlphaBetaFilter	A recurrent layer that can be used to smooth the input and estimate its derivative
Compressed	Fully connected layer with compressed weights
Convolutional	Applies a learnable filter on a 2D or 3D input
Dropout	Dropout mask
Extreme	Fully connected layer with fixed random weights
FullyConnected	Fully connected layer
Input	Input layer
OutputInfo	Provides information about the output of a layer
Layer	Interface that has to be implemented by all layers of a neural network that can be trained with backpropagation
LocalResponseNormalization	Local response normalization
MaxPooling	Performs max-pooling on 2D input feature maps
SigmaPi	Fully connected higher-order layer
Constraint	A helper class for specifying weight constrains in a higher-order neural network Derive a new class from this interface and simple reimplement the function call operator for the corresponding higher-order term
HigherOrderUnit
DistanceConstraint	Common constraint for encoding translation invariances into a SigmaPi layer
SlopeConstraint	Common constraint for encoding translation and scale invariances into a SigmaPi layer
TriangleConstraint	Common constraint for encoding translation, scale and rotation invariance into a SigmaPi layer
AngleTuple
Subsampling	Performs average pooling on 2D input feature maps
Learner	Common base class of all learning algorithms
Net	Feedforward multilayer neural network
Normalization	Normalize data so that for each feature the mean is 0 and the standard deviation is 1
OpenANNLibraryInfo	Provides information about the OpenANN library
CG	Conjugate Gradient
IPOPCMAES	Evolution Strategies with Covariance Matrix Adaption and a restart strategy that increases the population size (IPOP-CMA-ES)
LBFGS	Limited storage Broyden-Fletcher-Goldfarb-Shanno
LMA	Levenberg-Marquardt Algorithm
MBSGD	Mini-batch stochastic gradient descent
Optimizable	Represents an optimizable object
Optimizer	The common interface of all optimization algorithms
StoppingCriteria	Stopping criteria for optimization algorithms
StoppingInterrupt	A system-independent interface for checking interrupts that can signals the end of the optimization process externally
PCA	Principal component analysis
RBM	Restricted Boltzmann Machine
Regularization	Holds all information related to regularization terms in an error function
ActionSpace	Represents the action space in a reinforcement learning problem
Agent	A (learning) agent in a reinforcement learning problem
Environment	A reinforcement learning environment
RandomAgent	Choses actions randomly
StateSpace	Represents the state space in a reinforcement learning problem
SparseAutoEncoder	A sparse auto-encoder tries to reconstruct the inputs from a compressed representation
Transformer	Common base for all transformations
OpenANNException	This exception is thrown for all logical errors that occur in OpenANN API calls that are not time critical
RandomNumberGenerator	A utility class that simplifies the generation of random numbers
ZCAWhitening	Zero phase component analysis whitening transformation
optimization
StoppingCriteria
Optimizer
MBSGD
LMA
CG
LBFGS
preprocessing
Normalization
PCA
ZCAWhitening
KMeans
Transformation
Compressor
sine
util
Log
RandomNumberGenerator
OpenANN
xor
BCIDataSet
BCIDataCache
CIFARLoader	Loads the CIFAR-10 dataset
CMAES
Decimator
Distorter	Creates distorted images
DoubleExponentialSmoothing
DoublePoleBalancing	In this environment the agent has to control a cart such that the two poles mounted at the top of the cart do not pass a defined angle threshold
DoublePoleBalancingVisualization
IDXLoader
NeuroEvolutionAgent
Parameters
SinglePoleBalancing	In this environment the agent has to control a cart such that the pole mounted at the top of the cart does not pass a defined angle threshold
Stopwatch
TwoSpiralsDataSet
TwoSpiralsVisualization