Proposals:Refactoring Statistics Framework 2007 Background: Difference between revisions
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## Image | ## Image | ||
## Data points | ## Data points | ||
#Membership | #Membership models | ||
## Can be manually set or automatically generated from the sample data | ## Can be manually set or automatically generated from the sample data | ||
## Estimators are available to generate membership functions ( ImageModelEstimatorBase, ImageGuassianModelEstimator,ExpectationMaximizationMixtureModelEstimator ) | ## Estimators are available to generate membership functions ( ImageModelEstimatorBase, ImageGuassianModelEstimator,ExpectationMaximizationMixtureModelEstimator ) | ||
## Some classes are named with Estimator suffix but they do more than just estimating membership functions | ## Some classes are named with Estimator suffix but they do more than just estimating membership functions | ||
### itkKdTreeBasedKmeansEstimator | ### itkKdTreeBasedKmeansEstimator | ||
# | # Distance functions | ||
# Decision Rules | |||
# Classifiers | # Classifiers | ||
Note: | |||
# Classifiers provide interface that integrates all the other components. Classifiers provide a common framework | |||
# ITK also contains classes which combine specific types of the different components into one Huge framework such as itkScalarImageKmeansImageFilter and itkBayesianClassifierImageFilter. | |||
## itkScalarImageKmeansImageFilter: EuclideanDistance, KdTreeBasedKmeansEstimator, SampleClassifier, MinimumDecisionRule | |||
## itkBayesianClassifierImageFilter: Bayesian Estimator, MaximumDecisionRule | |||
Latest revision as of 21:19, 16 July 2008
The main components of a classification framework are
- Input
- Image
- Data points
- Membership models
- Can be manually set or automatically generated from the sample data
- Estimators are available to generate membership functions ( ImageModelEstimatorBase, ImageGuassianModelEstimator,ExpectationMaximizationMixtureModelEstimator )
- Some classes are named with Estimator suffix but they do more than just estimating membership functions
- itkKdTreeBasedKmeansEstimator
- Distance functions
- Decision Rules
- Classifiers
Note:
- Classifiers provide interface that integrates all the other components. Classifiers provide a common framework
- ITK also contains classes which combine specific types of the different components into one Huge framework such as itkScalarImageKmeansImageFilter and itkBayesianClassifierImageFilter.
- itkScalarImageKmeansImageFilter: EuclideanDistance, KdTreeBasedKmeansEstimator, SampleClassifier, MinimumDecisionRule
- itkBayesianClassifierImageFilter: Bayesian Estimator, MaximumDecisionRule
