trait Inference[Datum] extends Serializable
Inference is the core interface in Epic. It produces instances of epic.framework.Marginal which are then turned into epic.framework.ExpectedCounts.
There are two kinds of marginals produced by an inference object: gold and guess. Gold marginals are the marginals conditioned on the output label/structure itself (e.g. the parse tree). Guess marginals are the marginals conditioned on only the input data (e.g. the words in the sentence)
In structured prediction, the objective usually takes the form: \minimize \sum_{all structures} score(structure) - \sum_{all structures compatible with output label} score(structure)
with the derivative being: E_{all structures} features(structure) - E_{all structures compatible with output label} features(structure)
replacing sum with max for max marginals.
- Datum
the kind of thing to do inference on
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- abstract type Marginal <: framework.Marginal
- abstract type Scorer
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abstract
def
goldMarginal(scorer: Scorer, v: Datum): Marginal
Produces the "gold marginal" which is the marginal conditioned on the output label/structure itself.
Produces the "gold marginal" which is the marginal conditioned on the output label/structure itself.
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the example
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gold marginal
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abstract
def
marginal(scorer: Scorer, v: Datum): Marginal
Produces the "guess marginal" which is the marginal conditioned on only the input data
Produces the "guess marginal" which is the marginal conditioned on only the input data
- v
the example
- returns
gold marginal
- abstract def scorer(v: Datum): Scorer
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- def forTesting: Inference[Datum]
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- def marginal(v: Datum): Marginal
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