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