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## Uses of Class
calhoun.analysis.crf.CRFInference.InferenceResult

Packages that use CRFInference.InferenceResult
calhoun.analysis.crf | the interface, main `Conrad` class, and solver for the Conrad engine.
calhoun.analysis.crf.solver | training and inference algorithms used in the CRF engine

Uses of CRFInference.InferenceResult in calhoun.analysis.crf

Methods in calhoun.analysis.crf that return CRFInference.InferenceResult
`CRFInference.InferenceResult` | `Conrad.predict(InputSequence data)` preforms inference on the input sequence and determines the best labeling for the sequence using the configured inference algorithm.
`CRFInference.InferenceResult` | `CRFInference.predict(ModelManager mm, InputSequence<?> data, double[] weights)` Return the labelling that maximizes the conditional probability P(y|x).

Uses of CRFInference.InferenceResult in calhoun.analysis.crf.solver

Methods in calhoun.analysis.crf.solver that return CRFInference.InferenceResult
`CRFInference.InferenceResult` | `Viterbi.predict(ModelManager fm, InputSequence<?> seq, double[] lambda)`
`CRFInference.InferenceResult` | `SemiMarkovViterbiNoCache.predict(ModelManager fm, InputSequence<?> seq, double[] lambda)`
`CRFInference.InferenceResult` | `SemiMarkovViterbi.predict(ModelManager fm, InputSequence<?> seq, double[] lambda)`

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