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C

calcFeatureScore(Map<Boolean, Double>, Map<Boolean, Double>) - Method in class szte.csd.indicatorsel.CondEntropyIndicatorSelector
 
calcFeatureScore(Map<Boolean, Double>, Map<Boolean, Double>) - Method in class szte.csd.indicatorsel.MutualInfoIndicatorSelector
 
calcFeatureScore(Map<Boolean, Double>, Map<Boolean, Double>) - Method in class szte.csd.indicatorsel.ProbIndSel
 
ClassificationResult - Class in szte.datamining
 
ClassificationResult() - Constructor for class szte.datamining.ClassificationResult
 
ClassificationResult(DataHandler) - Constructor for class szte.datamining.ClassificationResult
 
classifyDataset(Model) - Method in class szte.datamining.DataHandler
 
classifyDataset(Model) - Method in class szte.datamining.mallet.MalletDataHandler
 
CMCDataHolder - Class in szte.io
The reader and container class for the CMC XML format.
CMCDataHolder() - Constructor for class szte.io.CMCDataHolder
 
CMCDocument - Class in szte.io
 
CMCDocument() - Constructor for class szte.io.CMCDocument
 
CMCRuleBased - Class in szte.csd.baseline
This fine-tuned hand-crafted rule-set was developed to CMC clinical NLP challenge in 2007.
CMCRuleBased() - Constructor for class szte.csd.baseline.CMCRuleBased
 
CondEntropyIndicatorSelector - Class in szte.csd.indicatorsel
The conditonal entropy indicator evaluator.
CondEntropyIndicatorSelector() - Constructor for class szte.csd.indicatorsel.CondEntropyIndicatorSelector
 
ContentShiftDetector - Class in szte.csd
The main entry point of the project.
ContentShiftDetector(Properties) - Constructor for class szte.csd.ContentShiftDetector
 
ContentShiftDetector() - Constructor for class szte.csd.ContentShiftDetector
 
CorpusStat - Class in szte.io
CorpusStat counts basic statistics (size, #labels, #avg. labels/doc etc) about the multi-labeling corpora (using the DocumentSet interface).
CorpusStat() - Constructor for class szte.io.CorpusStat
 
createEmptyDataHandler() - Method in class szte.datamining.DataHandler
 
createNewDataset(Map<String, Object>) - Method in class szte.datamining.DataHandler
creates a new empty dataset using the underlying native datatype
createNewDataset(Map<String, Object>) - Method in class szte.datamining.mallet.MalletDataHandler
 
createSubset(Set<String>, Set<String>) - Method in class szte.datamining.DataHandler
creates a subset of the dataset where only the given instances and/or features are present
createSubset(Set<String>, Set<String>) - Method in class szte.datamining.mallet.MalletDataHandler
 
crossvalidate(String, String) - Static method in class szte.csd.indicatorsel.TresholdOptimizer
Determines the best T threshold on the given task's training set for the indicator selection method is.
crossvalidateAll() - Static method in class szte.csd.indicatorsel.TresholdOptimizer
Determines the best T threshold on all task's training set for each indicator selection method (it takes several hours).
CSDModel - Class in szte.csd
CSDModel stores everything for an indicator selection and local context detection model.
CSDModel() - Constructor for class szte.csd.CSDModel
 
CSDModel(String, int) - Constructor for class szte.csd.CSDModel
 

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