| ►CAssignable | |
| Cfaif::DomainConcept< Dom > | Domain concept |
| Cfaif::ml::BeliefConcept< Bel > | Belief concept |
| Cfaif::ValueConcept< Val > | Value concept |
| Cfaif::ml::Belief< Val > | Belief is value id with probability |
| ►Cbinary_function | |
| Cfaif::ml::NormalizationFunctor< Belief, EvidenceValue > | |
| Cfaif::search::BooleanGene | |
| Cfaif::dna::Chain | The DNA strand (single) |
| ►Cfaif::ml::Classifier< Val > | Clasiffier interface |
| Cfaif::ml::DecisionTree< Val > | Decision Tree Classifier |
| Cfaif::ml::KNearestNeighbor< Val, Distance > | K Nearest Neighbor classifier |
| Cfaif::ml::NaiveBayesian< Val > | Naive Bayesian Classifier |
| Cfaif::ml::RandomForest< Val > | Random Forest Classifier |
| Cfaif::dna::CodonAminoTable | Codons for given amino, amino for given codon, singleton |
| Cfaif::search::compareWeight< T > | Comparizon used by searchUnifiedCost |
| Cfaif::search::compareWeightAndHeuristic< T > | Comparizon used by AStar |
| ►Cstd::vector< T >::const_iterator | STL iterator class |
| Cfaif::dna::Chain::const_iterator | |
| ►CCopyConstructible | |
| Cfaif::DomainConcept< Dom > | Domain concept |
| Cfaif::ml::BeliefConcept< Bel > | Belief concept |
| Cfaif::ValueConcept< Val > | Value concept |
| Cfaif::search::CrossoverCustom< Space > | Crossover policy - crossover from Space |
| Cfaif::search::CrossoverNone< Space > | Crossover policy - no crossover |
| Cfaif::ml::DecisionTreeTrainParams | Param for training decision tree |
| ►CDefaultConstructible | |
| Cfaif::DomainConcept< Dom > | Domain concept |
| Cfaif::ml::BeliefConcept< Bel > | Belief concept |
| Cfaif::ValueConcept< Val > | Value concept |
| Cfaif::ml::DistanceNominalValue< Val > | Distance metrics for Nomianal Values Collection, used in K Nearest Neighbors classifier |
| Cfaif::DistrValue | |
| Cfaif::DomainEnumerate< Val > | Forward declaration |
| Cfaif::dna::EnergyNucleo | Maps between pair of nucleotides and its energy |
| ►CEqualityComparable | |
| Cfaif::DomainConcept< Dom > | Domain concept |
| Cfaif::search::NodeWithChildrenConcept< Node > | Concept for node with children |
| Cfaif::search::NodeWithFinalFlagConcept< Node > | Concept for node with final flag for search in tree-like structures The function 'searchDepthFirst' and 'searchBreadthFirst' require this concept |
| Cfaif::ValueConcept< Val > | Value concept |
| Cfaif::search::EvolutionaryAlgorithm< Space, Mutation, Crossover, Selection, StopCondition > | Evolutionary algorithm |
| Cfaif::search::EvolutionaryAlgorithmGeneConcept< T > | Concept for evolutionary algorithm gene the type gives the generateRandom method and the mutate method |
| ►Cfaif::search::EvolutionaryAlgorithmSpaceConcept< Space > | Concept for evolutionary algorithm space |
| Cfaif::search::EvolutionaryAlgorithmSpaceWithCrossoverConcept< Space > | Concept for evolutionary algorithm space |
| Cfaif::search::EvolutionaryAlgorithmSpaceWithMutationConcept< Space > | Concept for evolutionary algorithm space |
| ►Cstd::exception | STL class |
| ►Cfaif::FaifException | Base exception class for faif library |
| Cfaif::dna::CodonStringTooShortException | Exception when chain representing codon is shorted than 3 nucleotides |
| Cfaif::dna::NucleotideBadCharException | Exception thrown when unknown nucleotide (bad letter) occures |
| Cfaif::NotFoundException | Exception thrown when the value for given attribute is not found |
| Cfaif::timeseries::PredictionRangeException | Bad prediction range exception |
| Cfaif::search::ExpectationCustom< Space > | Expectation policy - custiom |
| Cfaif::search::ExpectationMaximization< Space, Expectation, Maximization, StopCondition > | Expectation-Maximization algorithm |
| Cfaif::search::ExpectationNone< Space > | Expectation policy (empty) |
| Cfaif::FeatureInitDefault< Feature > | Feature init policy - use default constructor |
| Cfaif::dna::FoldedMatrixStrategy | |
| Cfaif::ml::FusionInternal< Belief > | Typedef's for Dempster-Shafer combination rule (for fusion) and some internal (helping) methods |
| Cfaif::search::HillClimbing< Space, NextNodeStrategy > | Hill climbing algorithm. Search the neighbour for the better solution |
| Cfaif::ml::Classifier< Val >::InitValueId< Feature > | Helping inner class to init PointAndFeature structure using getUnknownId method |
| ►Cstd::vector< T >::iterator | STL iterator class |
| Cfaif::dna::Chain::iterator | |
| Cfaif::dna::lessComplementary | |
| ►Cstd::list< T > | STL class |
| Cfaif::Space< Domain > | Space n-dimensional, each domain of the same type |
| Cfaif::Space< AttrDomain > | |
| Cfaif::search::MaximizationCustom< Space > | Maximization policy - custiom |
| Cfaif::search::MaximizationNone< Space > | Maximization policy (empty) n |
| Cfaif::search::MutationCustom< Space > | Mutation policy - mutation from Space |
| Cfaif::search::MutationNone< Space > | Mutation policy - no mutation |
| Cfaif::search::NextNodeCheckAll< Space > | Policy class for HillClimbing, check all neighbours |
| Cfaif::search::Node< Individual > | Struct to create node in search space from individual |
| Cfaif::search::Node< T > | |
| ►Cfaif::nominal_tag | Nominal attribute trait (equality comparable), modeled as element in unordered set |
| ►Cfaif::ordinal_tag | Ordered attribute trait (equality comparable, less than comparable) , modeled as element in ordered set |
| ►Cfaif::interval_tag | Interval attribute trait (equality comparable, less than comparable, distance), integer numbers |
| Cfaif::ratio_tag | Nominal attribute trait (equality comparable, less than comparable, distance, continuous), real numbers |
| ►Cnoncopyable | |
| Cfaif::dna::FoldedChain | DNA strand with secondary structure |
| Cfaif::dna::FoldedMatrix | |
| Cfaif::dna::FoldedPair | Two DNA chains with secondary structures |
| Cfaif::dna::Matrix | Matrix - 2D array with indexing |
| Cfaif::dna::SecStructProxy | |
| ►Cfaif::timeseries::Prediction | |
| Cfaif::timeseries::PredictionAR | |
| Cfaif::timeseries::PredictionKNN | |
| Cfaif::dna::Nucleotide | DNA nucleotide |
| ►Cpair | |
| Cfaif::dna::ConnectPair | The pair of nucleotides which are join by Watson-Crick interaction |
| Cfaif::hapl::AlleleImpl | Helping structure, implements the Allele members |
| Cfaif::timeseries::Section< V > | |
| Cfaif::timeseries::PredictionVisitor | |
| Cfaif::ml::PrintCountAttrFunctor< Categories > | Class to show the classifier state, print the attribs and counters |
| Cfaif::ml::PrintCountersFunctor< Categories > | Print the cauters for given category |
| Cfaif::RandomCustomCreator | |
| Cfaif::RandomCustomDistr | Distribution described by histogram (sum of ranges) |
| Cfaif::RandomDouble | Uniform distribution for double, in given range, e.g. <0,1), uses RandomSingleton |
| Cfaif::ml::RandomForestParams | Random forest's parameters |
| Cfaif::RandomInt | Uniform distribution for int, in range <min,max>, uses RandomSingleton |
| Cfaif::RandomNormal | Normal distribution for double, for given mean (mi) and standard deviation (sigma), uses RandomSingleton |
| Cfaif::RandomSingleton | Singleton, synchronized proxy to boost::Random |
| Cfaif::dna::SecStruct | Secondary structure |
| Cfaif::search::SelectionRanking< Space > | Succession and selection policy - the n-th best individuals survive |
| Cfaif::search::SelectionRoulette< Space > | Succession and selection policy - roulette wheel (probability of selection of an idividual is equal to its normalized fitness) |
| ►Cfaif::search::Space< Ind > | Typedef-s for space, where the fitness is defined as double |
| Cfaif::search::EvolutionaryAlgorithmSpace< Ind > | Typedef-s for space for evolutionary algorithm, where the population is a vector of individuals, and the fitness is the double |
| Cfaif::search::SpaceConcept< Space > | Concept for space with fitness |
| Cfaif::search::StopAfterNSteps< STEPS_NUM > | Stop condition, finish the algorithm after STEPS_NUM iterations |
| Cfaif::ml::SvmClassifier< Val, DomainVal > | |
| Cfaif::ml::TrainExampleCategoryCounters< Val > | |
| Cfaif::timeseries::Transformation | Transformation - class to change timeseries stored in TimeSeriesDigit and/or TimeSeriesReal |
| ►Cfaif::search::TransformationNoneTag | Trait tag, no transformation should be executed |
| Cfaif::search::TransformationCustomTag | Trait tag, user tranformation should be executed |
| Cfaif::search::TreeNode< T > | Template to create the node in tree-based search methods |
| Cfaif::search::TreeNodeHeuristicConcept< Node > | Concept for heuristic search algorithms, it check the presence of 'getHeuristic' method, used by heuristic search functions e.g. 'searchAStar' |
| Cfaif::search::TreeNodeWeightConcept< Node > | Concept for informed search algorithms, it check the presence of 'getWeight' method, used by informed search functions e.g. 'searchUniformCost' |
| ►Ctuple | |
| Cfaif::dna::Codon | Triplet of nucleotides, codon |
| Cfaif::timeseries::KNNDef | KNN parameters, k = num_neighbours, ref_size = size of reference block |
| Cfaif::timeseries::TimeValueDigit | |
| Cfaif::timeseries::TimeValueReal | Timeseries value, single value in given real time. Plain old data |
| ►Cunary_function | |
| Cfaif::ml::AddEvidenceFunctor< Belief > | |
| Cfaif::ValueNominal< Val > | Nominal attribute template (equality comparable) |
| ►Cstd::vector< T > | STL class |
| Cfaif::ml::Classifier< Val >::ExamplesTrain | Inner class - examples train collection |
| Cfaif::Point< Val > | Point in n-space, each component of the same type |
| Cfaif::timeseries::Discretizer< V > | |
| Cfaif::timeseries::TimeSeriesDigit | |
| Cfaif::timeseries::TimeSeriesReal | Timeseries - time hold as RealTime |
| ►Cfaif::Point< Value > | |
| Cfaif::PointAndFeature< Value, Feature, FeatureInit > | Point and some feature |
| Cfaif::search::VectorIndividual< Gene > | Template to generate individual which is the vector of Genes |
| Cfaif::search::VoseAlg | Helping class implemented the M.D.Vose (1991) algorithm |
| CDomain | |
| CSection< V > | |
| CValueId | |
