Proposals:Refactoring Statistics Framework 2007 Background: Difference between revisions

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## 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
# Decison Rule (Classifier ): such as
# Decison Rules
 
# Classifiers
 
Typical scenario
# Use an estimator to generate class models for input data.
# Use the generated class models, distance function and a decision rule to determine which class your
input belongs to.

Revision as of 21:08, 16 July 2008

DudaClassifier.png StatisticalClassificationFramework.png


The main components of a classification framework are

  1. Input
    1. Image
    2. Data points
  2. Membership function
    1. Distance functions
    2. Can be manually set or automatically generated from the sample data
    3. Estimators are available to generate membership functions ( ImageModelEstimatorBase, ImageGuassianModelEstimator,ExpectationMaximizationMixtureModelEstimator )
    4. Some classes are named with Estimator suffix but they do more than just estimating membership functions
      1. itkKdTreeBasedKmeansEstimator
  3. Decison Rules
  4. Classifiers
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