Compounds |
| class | Iterator |
| 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 ListSampleBase 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 native implementation of the ListSampleBase. More...
|
| class | ListSampleBase |
| | 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 | ListSampleToHistogramGenerator |
| | Generates a Histogram using the data from the ListSample object. More...
|
| class | LogLikelihoodGoodnessOfFitFunction |
| | calculates loglikelihood ratio statistics. More...
|
| class | MahalanobisDistanceMembershipFunction |
| | MahalanobisDistanceMembershipFunction class represents MahalanobisDistance Density Function. 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 ListSampleBase interfaces to ITK PointSet. 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) |
