Proposals:Refactoring Statistics Framework 2007 New Statistics Framework: Difference between revisions
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| Line 144: | Line 144: | ||
FunctionBase -> MembershipFunctionBase | FunctionBase -> MembershipFunctionBase | ||
FunctionBase -> DistanceMetric | FunctionBase -> DistanceMetric | ||
DistanceMetric -> MahalanobisDistanceMetric | DistanceMetric -> MahalanobisDistanceMetric | ||
DistanceMetric -> EuclideanDistanceMetric | DistanceMetric -> EuclideanDistanceMetric | ||
Revision as of 20:46, 17 July 2008
Class Manifesto of New Statistics Framework
Summary Table
The classes that integrate the new statistics framework are categorized in the following table
| Conceptual Class | Number |
|---|---|
| Traits | 1 |
| Data Objects | 4 |
| Filters | 11 |
| Total | 16 |
List of Classes per Category
Traits
- MeasurementVectorTraits
Data Objects
- Sample
- ListSample
- Histogram
- Subsample
Filters
- SampleToHistogramFilter
- MeanFilter
- WeightedMeanFilter
- CovarianceFilter
- WeightedCovarianceFilter
- HistogramToTextureFeaturesFilter
- ImageToListSampleFilter
- ScalarImageToCooccurrenceMatrixFilter
- SampleToSubsampleFilter
- SampleClassifierFilter
- NeighborhoodSubsampler
Classifiers (Suggested Design)
Elements
- MembershipFunctionBase
- DistanceToCentroidMembershipFunction (plugs in a DistanceMetric)
- DistanceMetrics
- Euclidean
- Mahalanobis
- 1_1
Filters
- Sample, Array of Membership Functions --> MembershipSample(sample,labels) == SampleClassifierFilter
- Sample, Array of Membership Functions --> GoodnessOfFitComponent (sample,weights) == SampleGoodnessOfFitFilter
Class Diagrams
Traits
Data Objects
Filters
Classifiers (Suggested Design)
