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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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