| Nalps | Contains support functions for the ALPS algorithm |
| Nout | Contains flags and manipulators to control the output format of individuals |
| ►Nvita | The main namespace for the project |
| ►Nalps | |
| Cparameters | Parameters for the Age-Layered Population Structure (ALPS) paradigm |
| ►Nboolean | |
| Cl_and | |
| Cl_not | |
| Cl_or | |
| Cone | |
| Czero | |
| ►Nexception | Groups the custom exceptions used in Vita |
| Cdata_format | |
| Cinsufficient_data | |
| ►Nga | |
| Cinteger | |
| Creal | Mainly used for differential evolution |
| ►Ninteger | Integer overflow is undefined behaviour |
| Cadd | |
| Cdiv | |
| Cife | |
| Cifl | |
| Cifz | |
| Cmod | |
| Cmul | |
| Cnumber | Integer ephemeral random constant |
| Cshl | |
| Csub | |
| ►Nout | |
| Cprint_format | |
| Nrandom | |
| ►Nreal | We assume that errors during floating-point operations aren't terminal errors |
| Cabs | The absolute value of a real number |
| Cadd | Sum of two real numbers |
| Caq | Analytic quotient (AQ) |
| Ccos | cos() of a real number |
| Cdiv | Unprotected division (UPD) between two real numbers |
| Cgt | "Greater Than" operator |
| Cidiv | Quotient of the division between two real numbers |
| Cifb | "If between" operator |
| Cife | "If equal" operator |
| Cifl | "If less then" operator |
| Cifz | "If zero" operator |
| Cinteger | Ephemeral random integer constant |
| Clength | Length of a string |
| Cln | Natural logarithm of a real number |
| Clt | "Less Then" operator |
| Cmax | The larger of two floating point values |
| Cmod | Remainder of the division between real numbers |
| Cmul | Product of real numbers |
| Creal | Ephemeral random constant |
| Csigmoid | Sigmoid function |
| Csin | Sin() of a real number |
| Csqrt | Square root of a real number |
| Csub | Subtraction between real numbers |
| ►Nrecombination | |
| Cbase | This class defines the program skeleton of a standard genetic programming crossover plus mutation operation |
| Cde | This is based on the differential evolution four members crossover |
| Cstrategy | The operation strategy (crossover, recombination, mutation...) adopted in the evolution class |
| ►Nreplacement | |
| Calps | ALPS based replacement scheme |
| Cfamily_competition | A family competition replacement scheme |
| Cpareto | |
| Cstrategy | The replacement strategy (random, tournament...) for the vita::evolution_strategy class |
| Ctournament | Tournament based replacement scheme (aka kill tournament) |
| ►Nselection | |
| Calps | Alps selection as described in https://github.com/ghornby/alps (see also vita::basic_alps_es for further details) |
| Cpareto | Pareto tournament selection as described in "Pursuing the Pareto
Paradigm" (Mark Kotanchek, Guido Smits, Ekaterina Vladislavleva) |
| Crandom | Pick a set of random individuals |
| Cstrategy | The strategy (tournament, fitness proportional...) for the evolution class |
| Ctournament | Tournament selection is a method of selecting an individual from a population of individuals |
| Nserialize | |
| ►Nstr | |
| Cife | String comparison for equality |
| Caccuracy_metric | Accuracy refers to the number of training examples that are correctly valued/classified as a proportion of the total number of examples in the training set |
| ►Canalyzer | Analyzer takes a statistics snapshot of a population |
| Csym_counter | |
| Cas_is_validation | A "null object" implementation of validation_strategy |
| Cbasic_alps_es | Basic ALPS strategy |
| Cbasic_binary_lambda_f | Lambda class for Binary Classification |
| Cbasic_binary_lambda_f< team< T >, S, N > | Binary Classification specialization for teams |
| Cbasic_class_lambda_f | The basic interface of a classification lambda class |
| Cbasic_dyn_slot_lambda_f | Lambda class for Slotted Dynamic Class Boundary Determination |
| Cbasic_dyn_slot_lambda_f< team< T >, S, N > | Slotted Dynamic Class Boundary Determination specialization for teams |
| Cbasic_fitness_t | A value assigned to an individual which reflects how well the individual solves the task |
| Cbasic_ga_search | Search driver for GAs |
| Cbasic_gaussian_lambda_f | Lambda class for the Gaussian Distribution Classification |
| Cbasic_gaussian_lambda_f< team< T >, S, N > | Gaussian Distribution Classification specialization for teams |
| Cbasic_gene | A gene is a unit of heredity in a living organism |
| Cbasic_lambda_f | The basic interface of a lambda function |
| Cbasic_reg_lambda_f | Lambda function specialized for regression tasks |
| Cbasic_src_lambda_f | Extends basic_lambda_f interface adding some useful methods for symbolic regression / classification and serialization |
| Cbinary_evaluator | Single class evaluator for classification problems |
| Ccache | Implements a hash table that links individuals' signature to fitness (mainly used by the evaluator_proxy class) |
| Ccached_evaluator | |
| Ccategory_info | |
| Ccategory_set | Information about the set of categories used in a specific problem |
| Cclassification_evaluator | This class is used to factorized out some code of the classification evaluators |
| Cclassification_result | Contains a class ID / confidence level pair |
| Cconstant | A constant value in a given domain |
| Cconstant< std::string > | |
| Cconstrained_evaluator | The class merges a basic evaluator and a penalty function into a new combined evaluator |
| Ccore_class_lambda_f | The model_metric class choose the appropriate method considering this type |
| Ccore_interpreter | Minimum interface of an interpreter |
| Ccore_reg_lambda_f | The model_metric class choose the appropriate method considering this type |
| Ccount_error_functor | Number of matches functor |
| Ccount_evaluator | Evaluator based on the number of matches |
| ►Cdataframe | A 2-dimensional labeled data structure with columns of potentially different types |
| ►Ccolumns_info | Information about the collection of columns (type, name, output index) |
| Ccolumn_info | Information about a single column of the dataset |
| Cexample | Stores a single element (row) of the dataset |
| Cparams | |
| Cde_alps_es | Differential evolution strategy enhanced with ALPS |
| Cde_es | Differential evolution strategy |
| Cde_problem | Provides a DE-specific interface to the generic problem class |
| Cdistribution | Simplifies the calculation of statistics regarding a sequence (mean, variance, standard deviation, entropy, min and max) |
| Cdss | Dynamic training Subset Selection |
| Cdyn_slot_evaluator | Slotted Dynamic Class Boundary Determination |
| ►Cenvironment | Context object aggregating multiple related parameters into one structure |
| Cde_parameters | |
| Cmep_parameters | |
| Cmisc_parameters | |
| Cstatistics | |
| Cteam_parameters | |
| Cevaluator | Calculates the fitness of an individual |
| Cevaluator_proxy | Provides a surrogate for an evaluator to control access to it |
| Cevolution | Progressively evolves a population of programs over a series of generations |
| Cevolution_strategy | Defines the skeleton of the evolution, deferring some steps to client subclasses |
| Cfunction | A symbol with arity() > 0 |
| Cga_evaluator | Calculates the fitness of an individual |
| Cga_problem | Provides a GA-specific interface to the generic problem class |
| Cgaussian_evaluator | Gaussian distribution for multiclass object classification |
| Chas_introns | The SFINAE way of recognizing if an individual has introns |
| Chas_introns< i_mep > | |
| Chash_t | A 128bit unsigned integer used as individual's signature / hash table look-up key |
| Choldout_validation | Holdout validation, aka one round cross-validation or conventional validation |
| Ci_de | An individual optimized for differential evolution |
| Ci_ga | An GA-individual optimized for combinatorial optimization |
| ►Ci_mep | A MEP (Multi Expression Programming) single member of a population |
| Cbasic_iterator | |
| Cindividual | A single member of a population |
| Cinterpreter | |
| Cinterpreter< i_mep > | A specialization of the core_interpreter class |
| Cis_team | |
| Cis_team< team< T > > | |
| Clocus | |
| Clog | A basic console printer with integrated logger |
| Cmae_error_functor | Mean Absolute Error |
| Cmae_evaluator | Evaluator based on the mean absolute error |
| Cmodel_measurements | A collection of measurements |
| Cmodel_metric | There are a lot of metrics related to a model (a lambda_f) and we don't want fat classes |
| Cmse_error_functor | Mean Squared Error |
| Cmse_evaluator | Evaluator based on the mean squared error |
| Cmurmurhash3 | MurmurHash3 (https://github.com/aappleby/smhasher) by Austin Appleby |
| Cnot_team | |
| Cnot_team< team< T > > | |
| ►Cpopulation | A group of individuals which may interact together (for example by mating) producing offspring |
| Cbase_iterator | |
| Cproblem | Aggregates the problem-related data needed by an evolutionary program |
| Crmae_error_functor | Mean of Relative Differences |
| Crmae_evaluator | Evaluator based on the mean of relative differences |
| Csearch | Search drives the evolution |
| Csearch_stats | |
| Csrc_evaluator | An evaluator specialized for symbolic regression / classification problems |
| Csrc_interpreter | |
| ►Csrc_problem | Provides a GP-specific interface to the generic problem class |
| Cdefault_symbols_t | |
| Csrc_search | Drives the search for solutions of symbolic regression / classification tasks |
| Cstd_es | Standard evolution strategy |
| Csum_of_errors_evaluator | An evaluator to minimize the sum of some sort of error |
| Csummary | A summary of evolution (results, statistics...) |
| Csymbol | Together functions and terminals are referred to as symbols |
| Csymbol_factory | An abstract factory for symbols |
| Csymbol_params | An interface for parameter passing to functions / terminals |
| Csymbol_set | A container for the symbols used by the GP engine |
| Cteam | A collection of cooperating individuals used as a member of vita::population |
| Cteam_class_lambda_f | An helper class for extending classification schemes to teams |
| Cterminal | A symbol with zero-arity |
| Ctest_evaluator | A fitness function used for debug purpose |
| Cvalidation_strategy | Interface for specific training / cross validation techniques (e.g |
| Cvariable | Represents an input argument (feature) for a symbolic regression or classification problem |
| Cwith_size | Tag representing size |
1.9.3