xcsf Directory Reference

Directories
	utils

Files
	__init__.py
	act_integer.c
	integer action functions.
	act_integer.h
	integer action functions.
	act_neural.c
	Neural network action functions.
	act_neural.h
	Neural network action functions.
	action.c
	Interface for classifier actions.
	action.h
	Interface for classifier actions.
	blas.c
	Basic linear algebra functions.
	blas.h
	Basic linear algebra functions.
	cl.c
	Functions operating on classifiers.
	cl.h
	Functions operating on classifiers.
	clset.c
	Functions operating on sets of classifiers.
	clset.h
	Functions operating on sets of classifiers.
	clset_neural.c
	Functions operating on sets of neural classifiers.
	clset_neural.h
	Functions operating on sets of neural classifiers.
	cond_dgp.c
	Dynamical GP graph condition functions.
	cond_dgp.h
	Dynamical GP graph condition functions.
	cond_dummy.c
	Always-matching dummy condition functions.
	cond_dummy.h
	Always-matching dummy condition functions.
	cond_ellipsoid.c
	Hyperellipsoid condition functions.
	cond_ellipsoid.h
	Hyperellipsoid condition functions.
	cond_gp.c
	Tree GP condition functions.
	cond_gp.h
	Tree GP condition functions.
	cond_neural.c
	Multi-layer perceptron neural network condition functions.
	cond_neural.h
	Multi-layer perceptron neural network condition functions.
	cond_rectangle.c
	Hyperrectangle condition functions.
	cond_rectangle.h
	Hyperrectangle condition functions.
	cond_ternary.c
	Ternary condition functions.
	cond_ternary.h
	Ternary condition functions.
	condition.c
	Interface for classifier conditions.
	condition.h
	Interface for classifier conditions.
	config.c
	Configuration file (JSON) handling functions.
	config.h
	Configuration file handling functions.
	dgp.c
	An implementation of dynamical GP graphs with fuzzy activations.
	dgp.h
	An implementation of dynamical GP graphs with fuzzy activations.
	ea.c
	Evolutionary algorithm functions.
	ea.h
	Evolutionary algorithm functions.
	env.c
	Built-in problem environment interface.
	env.h
	Built-in problem environment interface.
	env_csv.c
	CSV input file handling functions.
	env_csv.h
	CSV input file handling functions.
	env_maze.c
	The discrete maze problem environment module.
	env_maze.h
	The discrete maze problem environment module.
	env_mux.c
	The real multiplexer problem environment.
	env_mux.h
	The real multiplexer problem environment.
	gp.c
	An implementation of GP trees based upon TinyGP.
	gp.h
	An implementation of GP trees based upon TinyGP.
	image.c
	Image handling functions.
	image.h
	Image handling functions.
	loss.c
	Loss functions for calculating prediction error.
	loss.h
	Loss functions for calculating prediction error.
	main.c
	Main function for stand-alone binary execution.
	neural.c
	An implementation of a multi-layer perceptron neural network.
	neural.h
	An implementation of a multi-layer perceptron neural network.
	neural_activations.c
	Neural network activation functions.
	neural_activations.h
	Neural network activation functions.
	neural_layer.c
	Interface for neural network layers.
	neural_layer.h
	Interface for neural network layers.
	neural_layer_args.c
	Functions operating on neural network arguments/constants.
	neural_layer_args.h
	Functions operating on neural network arguments/constants.
	neural_layer_avgpool.c
	An implementation of an average pooling layer.
	neural_layer_avgpool.h
	An implementation of an average pooling layer.
	neural_layer_connected.c
	An implementation of a fully-connected layer of perceptrons.
	neural_layer_connected.h
	An implementation of a fully-connected layer of perceptrons.
	neural_layer_convolutional.c
	An implementation of a 2D convolutional layer.
	neural_layer_convolutional.h
	An implementation of a 2D convolutional layer.
	neural_layer_dropout.c
	An implementation of a dropout layer.
	neural_layer_dropout.h
	An implementation of a dropout layer.
	neural_layer_lstm.c
	An implementation of a long short-term memory layer.
	neural_layer_lstm.h
	An implementation of a long short-term memory layer.
	neural_layer_maxpool.c
	An implementation of a 2D maxpooling layer.
	neural_layer_maxpool.h
	An implementation of a 2D maxpooling layer.
	neural_layer_noise.c
	An implementation of a Gaussian noise adding layer.
	neural_layer_noise.h
	An implementation of a Gaussian noise adding layer.
	neural_layer_recurrent.c
	An implementation of a recurrent layer of perceptrons.
	neural_layer_recurrent.h
	An implementation of a recurrent layer of perceptrons.
	neural_layer_softmax.c
	An implementation of a softmax layer.
	neural_layer_softmax.h
	An implementation of a softmax layer.
	neural_layer_upsample.c
	An implementation of a 2D upsampling layer.
	neural_layer_upsample.h
	An implementation of a 2D upsampling layer.
	pa.c
	Prediction array functions.
	pa.h
	Prediction array functions.
	param.c
	Functions for setting and printing parameters.
	param.h
	Functions for setting and printing parameters.
	perf.c
	System performance printing.
	perf.h
	System performance printing.
	pred_constant.c
	Piece-wise constant prediction functions.
	pred_constant.h
	Piece-wise constant prediction functions.
	pred_neural.c
	Multi-layer perceptron neural network prediction functions.
	pred_neural.h
	Multi-layer perceptron neural network prediction functions.
	pred_nlms.c
	Normalised least mean squares prediction functions.
	pred_nlms.h
	Normalised least mean squares prediction functions.
	pred_rls.c
	Recursive least mean squares prediction functions.
	pred_rls.h
	Recursive least mean squares prediction functions.
	prediction.c
	Interface for classifier predictions.
	prediction.h
	Interface for classifier predictions.
	pybind_callback.h
	Interface for callbacks.
	pybind_callback_checkpoint.h
	Checkpoint callback for Python library.
	pybind_callback_earlystop.h
	Early stopping callback for Python library.
	pybind_utils.h
	Utilities for Python library.
	pybind_wrapper.cpp
	Python library wrapper functions.
	rule_dgp.c
	Dynamical GP graph rule (condition + action) functions.
	rule_dgp.h
	Dynamical GP graph rule (condition + action) functions.
	rule_neural.c
	Neural network rule (condition + action) functions.
	rule_neural.h
	Neural network rule (condition + action) functions.
	sam.c
	Self-adaptive mutation functions.
	sam.h
	Self-adaptive mutation functions.
	utils.c
	Utility functions for random number handling, etc.
	utils.h
	Utility functions for random number handling, etc.
	xcs_rl.c
	Reinforcement learning functions.
	xcs_rl.h
	Reinforcement learning functions.
	xcs_supervised.c
	Supervised regression learning functions.
	xcs_supervised.h
	Supervised regression learning functions.
	xcsf.c
	System-level functions for initialising, saving, loading, etc.
	xcsf.h
	XCSF data structures.