Uses of Class
edu.mit.nlp.segmenter.SegResult

Packages that use SegResult
edu.mit.nlp.segmenter   
edu.mit.nlp.segmenter.dp   
 

Uses of SegResult in edu.mit.nlp.segmenter
 

Methods in edu.mit.nlp.segmenter that return SegResult
static SegResult SegResult.getAvgResult(SegResult[] results)
           
static SegResult SegResult.getAvgResult(SegResult[] results, int test_index)
           
 

Methods in edu.mit.nlp.segmenter with parameters of type SegResult
static SegResult SegResult.getAvgResult(SegResult[] results)
           
static SegResult SegResult.getAvgResult(SegResult[] results, int test_index)
           
static void SegResult.printResults(PrintStream out, SegResult[] results, double[] priors)
           
 

Uses of SegResult in edu.mit.nlp.segmenter.dp
 

Methods in edu.mit.nlp.segmenter.dp that return SegResult
 SegResult[] DPSeg.segEM(double[] init_params)
          segEM estimates the parameters using a form of hard EM it computes the best segmentation given the current parameters, then does a gradient-based search for new parameters, and iterates.
 SegResult[] DPSeg.segment(double[] params)
          segment each document in the dataset.
protected  SegResult[] DPSeg.segmentKnown(double[] params)
          segment in the case that the number of segments per doc is known. same arguments as DPSeg.segment(double[])
protected  SegResult[] DPSeg.segmentUnknown(double[] params)
          segment in the case of an unknown number of segments. same arguments as DPSeg.segment(double[])
 



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