Proposals:Refactoring Statistics Framework 2007 Class Manifesto: Difference between revisions
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== Calculators == | == Calculators == | ||
API | === API === | ||
* SetInputSample() | * SetInputSample() | ||
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* GenerateData() | * GenerateData() | ||
* GetOutput() | * GetOutput() | ||
=== Class Diagram === | |||
<graphviz> | <graphviz> |
Revision as of 20:09, 4 April 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
- HypersphereKernelMeanShiftModeSeeker
- 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
Univariate Distributions
Algorithms
Calculators
API
- SetInputSample()
- GetInputSample()
- GetMeasurementVectorSize()
- SetMeasurementVectorSize()
- Update()
- GenerateData()
- GetOutput()
Class Diagram
Generators
API
- SetInputSample()
- GetImputSample()
Class Diagram
Filters
Multivariate Density Functions
Distance Metrics
Components
Estimators