Proposals:Refactoring Statistics Framework 2007 Class Manifesto: Difference between revisions
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== Process Objects == | == Process Objects == | ||
<graphviz> | |||
digraph G { | |||
LightProcessObject [URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1LightProcessObject.html"]; | |||
ClassifierBase [URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1ClassifierBase.html"]; | |||
SampleClassifier [shape=box,URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1Statistics_1_1SampleClassifier.html"]; | |||
SampleClassifierWithMask [shape=box,URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1Statistics_1_1SampleClassifierWithMask.html"]; | |||
LightProcessObject -> ClassifierBase | |||
ClassifierBase -> SampleClassifier | |||
ClassifierBase -> SampleClassifierWithMask | |||
} | |||
</graphviz> | |||
== Traits == | == Traits == | ||
Revision as of 12:45, 28 March 2007
Statistics Class Manifesto
Summary Table
They are categorized in the following table
| Conceptual Class | Number |
|---|---|
| Measurement Containers | 8 |
| Frequency Containers | 2 |
| Process Objects | 2 |
| Traits | 1 |
| Mean shift | 3 |
| Adaptors | 5 |
| Univariate Distributions | 4 |
| Algorithms | 3 |
| Calculators | 6 |
| Generators | 12 |
| Filters | 10 |
| Multivariate Density Functions | 8 |
| Distance Metrics | 2 |
| Components | 4 |
| Estimators | 2 |
| Total | 72 |
List of Classes per Category
Measurement Containers
- KdTree
- Histogram
- VariableDimensionHistogram
- ListSampleBase
- ListSample
- Sample
- Subsample
- MembershipSample
Frequency Containers
- DenseFrequencyContainer
- SparseFrequencyContainer
Process Objects
- SampleClassifier
- SampleClassifierWithMask
Traits
- MeasurementVectorTraits
MeanShift
- ypersphereKernelMeanShiftModeSeeker
- MeanShiftModeCacheMethod
- MeanShiftModeSeekerBase
Adaptors
- ImageToCooccurrenceListAdaptor
- ImageToListAdaptor
- JointDomainImageToListAdaptor
- PointSetToListAdaptor
- ScalarImageToListAdaptor
Univariate Distributions
- ChiSquareDistribution
- GaussianDistribution
- ProbabilityDistribution
- TDistribution
Algorithms
- SampleAlgorithmBase
- StatisticsAlgorithm
- NeighborhoodSampler
Calculators
- CovarianceCalculator
- GreyLevelCooccurrenceMatrixTextureCoefficientsCalculator
- MeanCalculator
- ScalarImageTextureCalculator
- WeightedCovarianceCalculator
- WeightedMeanCalculator
Generators
- ImageToHistogramGenerator
- ImageToListGenerator
- KdTreeGenerator
- ListSampleToHistogramGenerator
- MaskedScalarImageToGreyLevelCooccurrenceMatrixGenerator
- MembershipSampleGenerator
- NormalVariateGenerator
- RandomVariateGeneratorBase
- ScalarImageToGreyLevelCooccurrenceMatrixGenerator
- ScalarImageToHistogramGenerator
- SelectiveSubsampleGenerator
- WeightedCentroidKdTreeGenerator
Filters
* HistogramToEntropyImageFilter
- HistogramToImageFilter
- HistogramToIntensityImageFilter
- HistogramToLogProbabilityImageFilter
- HistogramToProbabilityImageFilter
- ListSampleToHistogramFilter
- SampleMeanShiftBlurringFilter
- SampleMeanShiftClusteringFilter
- SampleSelectiveMeanShiftBlurringFilter
- SampleToHistogramProjectionFilter
Multivariate Density Functions
* DensityFunction
- DistanceToCentroidMembershipFunction
- GaussianDensityFunction
- GoodnessOfFitFunctionBase
- GoodnessOfFitMixtureModelCostFunction
- LogLikelihoodGoodnessOfFitFunction
- MahalanobisDistanceMembershipFunction
- MembershipFunctionBase
Distance Metrics
- DistanceMetric
- EuclideanDistance
Components
- GaussianGoodnessOfFitComponent
- GaussianMixtureModelComponent
- GoodnessOfFitComponentBase
- MixtureModelComponentBase
Estimators
- ExpectationMaximizationMixtureModelEstimator
- KdTreeBasedKmeansEstimator
Class Diagrams
Measurement Containers
Frequency Containers
Process Objects
Traits
MeanShift
Adaptors
