▼N**faif** | |

►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) |