gnes.score_fn.normalize module¶
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class
gnes.score_fn.normalize.Normalizer1[source]¶ Bases:
gnes.score_fn.base.ModifierScoreFnDo normalizing: score = 1 / (1 + sqrt(score))
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train(*args, **kwargs)¶ Train the model, need to be overrided
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class
gnes.score_fn.normalize.Normalizer2(num_dim)[source]¶ Bases:
gnes.score_fn.base.ModifierScoreFnDo normalizing: score = 1 / (1 + score / num_dim)
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train(*args, **kwargs)¶ Train the model, need to be overrided
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class
gnes.score_fn.normalize.Normalizer3(num_dim)[source]¶ Bases:
gnes.score_fn.normalize.Normalizer2Do normalizing: score = 1 / (1 + sqrt(score) / num_dim)
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train(*args, **kwargs)¶ Train the model, need to be overrided
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class
gnes.score_fn.normalize.Normalizer4(num_bytes)[source]¶ Bases:
gnes.score_fn.base.ModifierScoreFnDo normalizing: score = 1 - score / num_bytes
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train(*args, **kwargs)¶ Train the model, need to be overrided
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class
gnes.score_fn.normalize.Normalizer5[source]¶ Bases:
gnes.score_fn.base.ModifierScoreFnDo normalizing: score = 1 / (1 + sqrt(abs(score)))
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train(*args, **kwargs)¶ Train the model, need to be overrided
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