| ▼Nfaif | |
| ►Ndna | Primitives for bioinformatics |
| ►CChain | The DNA strand (single) |
| Cconst_iterator | |
| Citerator | |
| CCodon | Triplet of nucleotides, codon |
| CCodonAminoTable | Codons for given amino, amino for given codon, singleton |
| CCodonStringTooShortException | Exception when chain representing codon is shorted than 3 nucleotides |
| CConnectPair | The pair of nucleotides which are join by Watson-Crick interaction |
| CEnergyNucleo | Maps between pair of nucleotides and its energy |
| CFoldedChain | DNA strand with secondary structure |
| CFoldedMatrix | |
| CFoldedMatrixStrategy | |
| CFoldedPair | Two DNA chains with secondary structures |
| ClessComplementary | |
| CMatrix | Matrix - 2D array with indexing |
| CNucleotide | DNA nucleotide |
| CNucleotideBadCharException | Exception thrown when unknown nucleotide (bad letter) occures |
| CSecStruct | Secondary structure |
| CSecStructProxy | |
| ►Nhapl | Population genetics (haplotype and marker analyzis) primitives and algorithms |
| CAlleleImpl | Helping structure, implements the Allele members |
| ►Nml | Machine learning namespace (mainly classifier algorithms) |
| CAddEvidenceFunctor | |
| CBelief | Belief is value id with probability |
| CBeliefConcept | Belief concept |
| ►CClassifier | Clasiffier interface |
| CExamplesTrain | Inner class - examples train collection |
| CInitValueId | Helping inner class to init PointAndFeature structure using getUnknownId method |
| CDecisionTree | Decision Tree Classifier |
| CDecisionTreeTrainParams | Param for training decision tree |
| CDistanceNominalValue | Distance metrics for Nomianal Values Collection, used in K Nearest Neighbors classifier |
| CFusionInternal | Typedef's for Dempster-Shafer combination rule (for fusion) and some internal (helping) methods |
| CKNearestNeighbor | K Nearest Neighbor classifier |
| CNaiveBayesian | Naive Bayesian Classifier |
| CNormalizationFunctor | |
| CPrintCountAttrFunctor | Class to show the classifier state, print the attribs and counters |
| CPrintCountersFunctor | Print the cauters for given category |
| CRandomForest | Random Forest Classifier |
| CRandomForestParams | Random forest's parameters |
| CSvmClassifier | |
| CTrainExampleCategoryCounters | |
| ►Nsearch | Namespace of searching algorithms and optimization algorithms |
| CBooleanGene | |
| CcompareWeight | Comparizon used by searchUnifiedCost |
| CcompareWeightAndHeuristic | Comparizon used by AStar |
| CCrossoverCustom | Crossover policy - crossover from Space |
| CCrossoverNone | Crossover policy - no crossover |
| CEvolutionaryAlgorithm | Evolutionary algorithm |
| CEvolutionaryAlgorithmGeneConcept | Concept for evolutionary algorithm gene the type gives the generateRandom method and the mutate method |
| CEvolutionaryAlgorithmSpace | Typedef-s for space for evolutionary algorithm, where the population is a vector of individuals, and the fitness is the double |
| CEvolutionaryAlgorithmSpaceConcept | Concept for evolutionary algorithm space |
| CEvolutionaryAlgorithmSpaceWithCrossoverConcept | Concept for evolutionary algorithm space |
| CEvolutionaryAlgorithmSpaceWithMutationConcept | Concept for evolutionary algorithm space |
| CExpectationCustom | Expectation policy - custiom |
| CExpectationMaximization | Expectation-Maximization algorithm |
| CExpectationNone | Expectation policy (empty) |
| CHillClimbing | Hill climbing algorithm. Search the neighbour for the better solution |
| CMaximizationCustom | Maximization policy - custiom |
| CMaximizationNone | Maximization policy (empty) n |
| CMutationCustom | Mutation policy - mutation from Space |
| CMutationNone | Mutation policy - no mutation |
| CNextNodeCheckAll | Policy class for HillClimbing, check all neighbours |
| CNode | Struct to create node in search space from individual |
| CNodeWithChildrenConcept | Concept for node with children |
| CNodeWithFinalFlagConcept | Concept for node with final flag for search in tree-like structures The function 'searchDepthFirst' and 'searchBreadthFirst' require this concept |
| CSelectionRanking | Succession and selection policy - the n-th best individuals survive |
| CSelectionRoulette | Succession and selection policy - roulette wheel (probability of selection of an idividual is equal to its normalized fitness) |
| CSpace | Typedef-s for space, where the fitness is defined as double |
| CSpaceConcept | Concept for space with fitness |
| CStopAfterNSteps | Stop condition, finish the algorithm after STEPS_NUM iterations |
| CTransformationCustomTag | Trait tag, user tranformation should be executed |
| CTransformationNoneTag | Trait tag, no transformation should be executed |
| CTreeNode | Template to create the node in tree-based search methods |
| CTreeNodeHeuristicConcept | Concept for heuristic search algorithms, it check the presence of 'getHeuristic' method, used by heuristic search functions e.g. 'searchAStar' |
| CTreeNodeWeightConcept | Concept for informed search algorithms, it check the presence of 'getWeight' method, used by informed search functions e.g. 'searchUniformCost' |
| CVectorIndividual | Template to generate individual which is the vector of Genes |
| CVoseAlg | Helping class implemented the M.D.Vose (1991) algorithm |
| ►Ntimeseries | TimeSeries (collection of triples<timestamp, value, quality>) tools |
| CDiscretizer | |
| CKNNDef | KNN parameters, k = num_neighbours, ref_size = size of reference block |
| CPrediction | |
| CPredictionAR | |
| CPredictionKNN | |
| CPredictionRangeException | Bad prediction range exception |
| CPredictionVisitor | |
| CSection | |
| CTimeSeriesDigit | |
| CTimeSeriesReal | Timeseries - time hold as RealTime |
| CTimeValueDigit | |
| CTimeValueReal | Timeseries value, single value in given real time. Plain old data |
| CTransformation | Transformation - class to change timeseries stored in TimeSeriesDigit and/or TimeSeriesReal |
| CDistrValue | |
| CDomainConcept | Domain concept |
| CDomainEnumerate | Forward declaration |
| CFaifException | Base exception class for faif library |
| CFeatureInitDefault | Feature init policy - use default constructor |
| Cinterval_tag | Interval attribute trait (equality comparable, less than comparable, distance), integer numbers |
| Cnominal_tag | Nominal attribute trait (equality comparable), modeled as element in unordered set |
| CNotFoundException | Exception thrown when the value for given attribute is not found |
| Cordinal_tag | Ordered attribute trait (equality comparable, less than comparable) , modeled as element in ordered set |
| CPoint | Point in n-space, each component of the same type |
| CPointAndFeature | Point and some feature |
| CRandomCustomCreator | |
| CRandomCustomDistr | Distribution described by histogram (sum of ranges) |
| CRandomDouble | Uniform distribution for double, in given range, e.g. <0,1), uses RandomSingleton |
| CRandomInt | Uniform distribution for int, in range <min,max>, uses RandomSingleton |
| CRandomNormal | Normal distribution for double, for given mean (mi) and standard deviation (sigma), uses RandomSingleton |
| CRandomSingleton | Singleton, synchronized proxy to boost::Random |
| Cratio_tag | Nominal attribute trait (equality comparable, less than comparable, distance, continuous), real numbers |
| CSpace | Space n-dimensional, each domain of the same type |
| CValueConcept | Value concept |
| CValueNominal | Nominal attribute template (equality comparable) |
