Proposals:Refactoring Statistics Framework 2007 Class Manifesto: Difference between revisions
From KitwarePublic
Jump to navigationJump to search
| Line 176: | Line 176: | ||
ListSample [shape=box,URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1Statistics_1_1ListSample.html"]; | ListSample [shape=box,URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1Statistics_1_1ListSample.html"]; | ||
VariableDimensionHistogram [shape=box,URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1Statistics_1_1VariableDimensionHistogram.html"]; | VariableDimensionHistogram [shape=box,URL="http://public.kitware.com/Insight/Doxygen/html/classitk_1_1Statistics_1_1VariableDimensionHistogram.html"]; | ||
Sample -> ListSampleBase; | Sample -> ListSampleBase; | ||
Sample -> Histogram; | Sample -> Histogram; | ||
| Line 187: | Line 182: | ||
Sample -> VariableDimensionHistogram; | Sample -> VariableDimensionHistogram; | ||
ListSampleBase -> ListSample; | ListSampleBase -> ListSample; | ||
} | } | ||
</graphviz> | </graphviz> | ||
== Process Objects == | == Process Objects == | ||
| Line 203: | Line 192: | ||
== Adaptors == | == Adaptors == | ||
== Univariate Distributions == | == Univariate Distributions == | ||
Revision as of 17:14, 26 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
Error writing graphviz file to disk.
Process Objects
Traits
MeanShift
Adaptors
Univariate Distributions
Algorithms
Calculators
Generators
Filters
Multivariate Density Functions
Distance Metrics
Components
Estimators
Frequency Containers
Error writing graphviz file to disk.
