Proposals:Refactoring Statistics Framework 2007 Class Manifesto: Difference between revisions
From KitwarePublic
Jump to navigationJump to search
Line 194: | Line 194: | ||
} | } | ||
</graphviz> | </graphviz> | ||
== Process Objects == | |||
== Traits == | |||
== MeanShift == | |||
== Adaptors == | |||
== Univariate Distributions == | |||
== Algorithms == | |||
== Calculators == | |||
== Generators == | |||
== Filters == | |||
== Multivariate Density Functions == | |||
== Distance Metrics == | |||
== Components == | |||
== Estimators == | |||
== Frequency Containers == | == Frequency Containers == |
Revision as of 17:06, 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
Process Objects
Traits
MeanShift
Adaptors
Univariate Distributions
Algorithms
Calculators
Generators
Filters
Multivariate Density Functions
Distance Metrics
Components
Estimators
Frequency Containers