Compounds | |
class | Iterator |
class | Iterator |
class | Iterator |
struct | Candidate |
class | CandidateVector |
class | CovarianceCalculator |
Calculates the covariance matrix of the target sample data. More... | |
class | DenseFrequencyContainer |
his class is a container for an histogram. More... | |
class | DensityFunction |
DensityFunction class defines common interfaces for density functions. More... | |
class | DistanceMetric |
this class declares common interfaces for distance functions. More... | |
class | DistanceToCentroidMembershipFunction |
DistanceToCentroidMembershipFunction class represents DistanceToCentroid Density Function. More... | |
class | EuclideanDistance |
class | ExpectationMaximizationMixtureModelEstimator |
Integration point for MembershipCalculator, DecisionRule, and target sample data. More... | |
class | GaussianDensityFunction |
GaussianDensityFunction class represents Gaussian Density Function. More... | |
class | GaussianGoodnessOfFitComponent |
provides implemenations of GoodnessOfFitComponentBase's methods for a Gaussian component. More... | |
class | GaussianMixtureModelComponent |
calculates sample mean. More... | |
class | GoodnessOfFitComponentBase |
provides component (module) type specific functionalities for GoodnessOfFitMixtureModelCostFunction. More... | |
class | GoodnessOfFitFunctionBase |
base class for classes calculates different types of goodness-of-fit statistics. More... | |
class | GoodnessOfFitMixtureModelCostFunction |
calculates the goodness-of-fit statstics for multivarate mixture model. More... | |
class | Histogram |
This class stores measurement vectors in the context of n-dimensional histogram. More... | |
class | Iterator |
class | ImageToListAdaptor |
This class provides ListSample interfaces to ITK Image. More... | |
class | Iterator |
class | KdTree |
KdTree. More... | |
class | KdTreeBasedKmeansEstimator |
fast k-means algorithm implementation using k-d tree structure. More... | |
class | KdTreeGenerator |
KdTreeGenerator. More... | |
struct | KdTreeNode |
struct | KdTreeNonterminalNode |
struct | KdTreeTerminalNode |
struct | KdTreeWeightedCenteroidNonterminalNode |
class | NearestNeighbors |
class | ListSample |
This class is the base class for containers that have a list of measurement vectors. More... | |
class | ListSampleToHistogramFilter |
Imports data from ListSample object to Histogram object. More... | |
class | LogLikelihoodGoodnessOfFitFunction |
calculates loglikelihood ratio statistics. More... | |
class | MahalanobisDistanceMembershipFunction |
MahalanobisDistanceMembershipFunction class represents MahalanobisDistance Density Function. More... | |
class | MaxDecisionRule |
A Decision rule that choose the class that has maximum value. More... | |
class | MeanCalculator |
calculates sample mean. More... | |
class | MembershipFunctionBase |
MembershipFunctionBase class declares common interfaces for membership functions. More... | |
class | MembershipSample |
Container for storing the instance-identifiers of other sample with their associated class labels. More... | |
class | MembershipSampleGenerator |
MembershipSampleGenerator generates a MembershipSample object using a class mask sample. More... | |
class | MixtureModelComponentBase |
base class for distribution modules that supports analytical way to update the distribution parameters. More... | |
class | NeighborhoodSampler |
generates a Subsample that is sampled from the input sample using a spherical kernel. More... | |
class | NormalVariateGenerator |
Normal random variate generator. More... | |
class | PointSetToListAdaptor |
This class provides ListSample interfaces to ITK Image. More... | |
class | PSquareQuantile |
Raj Jain's P-Square algorithm implementation. More... | |
class | RandomVariateGeneratorBase |
this class defines common interfaces for random variate generators. More... | |
class | Sample |
Sample defines common iterfaces for each subclasses. More... | |
class | SampleAlgorithmBase |
calculates sample mean. More... | |
class | SampleClassifier |
Integration point for MembershipCalculator, DecisionRule, and target sample data. More... | |
class | SampleToHistogramProjectionFilter |
projects measurement vectors on to an axis to generate an 1D histogram. More... | |
class | SparseFrequencyContainer |
his class is a container for an histogram. More... | |
class | Subsample |
class | TableLookupSampleClassifier |
Integration point for MembershipCalculator, DecisionRule, and target sample data with a pre-calculated look up table. More... | |
class | WeightedCenteroidKdTreeGenerator |
WeightedCenteroidKdTreeGenerator. More... | |
class | WeightedCovarianceCalculator |
Calculates the covariance matrix of the target sample data where each measurement vector has an associated weight value. More... | |
class | WeightedMeanCalculator |
calculates sample mean where each measurement vector has associated weight value. More... | |
Functions | |
template<class TSize> TSize | FloorLog (TSize size) |
template<class TValue> TValue | MedianOfThree (const TValue a, const TValue b, const TValue c) |
template<class TSample> void | FindSampleBound (TSample *sample, typename TSample::Iterator begin, typename TSample::Iterator end, typename TSample::MeasurementVectorType &min, typename TSample::MeasurementVectorType &max) |
template<class TSubsample> void | FindSampleBoundAndMean (TSubsample *sample, int beginIndex, int endIndex, typename TSubsample::MeasurementVectorType &min, typename TSubsample::MeasurementVectorType &max, typename TSubsample::MeasurementVectorType &mean) |
template<class TSubsample> int | Partition (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, const typename TSubsample::MeasurementType partitionValue) |
template<class TSubsample> TSubsample::MeasurementType | QuickSelect (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int kth, typename TSubsample::MeasurementType medianGuess) |
template<class TSubsample> TSubsample::MeasurementType | QuickSelect (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int kth) |
template<class TSubsample> void | InsertSort (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex) |
template<class TSubsample> void | DownHeap (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int node) |
template<class TSubsample> void | HeapSort (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex) |
template<class TSubsample> void | IntrospectiveSortLoop (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int depthLimit, int sizeThreshold) |
template<class TSubsample> void | IntrospectiveSort (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int sizeThreshold) |
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