gnes.score_fn.normalize module

class gnes.score_fn.normalize.Normalizer1[source]

Bases: gnes.score_fn.base.ModifierScoreFn

Do normalizing: score = 1 / (1 + sqrt(score))

train(*args, **kwargs)

Train the model, need to be overrided

class gnes.score_fn.normalize.Normalizer2(num_dim: int)[source]

Bases: gnes.score_fn.base.ModifierScoreFn

Do normalizing: score = 1 / (1 + score / num_dim)

train(*args, **kwargs)

Train the model, need to be overrided

class gnes.score_fn.normalize.Normalizer3(num_dim: int)[source]

Bases: gnes.score_fn.normalize.Normalizer2

Do normalizing: score = 1 / (1 + sqrt(score) / num_dim)

train(*args, **kwargs)

Train the model, need to be overrided

class gnes.score_fn.normalize.Normalizer4(num_bytes: int)[source]

Bases: gnes.score_fn.base.ModifierScoreFn

Do normalizing: score = 1 - score / num_bytes

train(*args, **kwargs)

Train the model, need to be overrided

class gnes.score_fn.normalize.Normalizer5[source]

Bases: gnes.score_fn.base.ModifierScoreFn

Do normalizing: score = 1 / (1 + sqrt(abs(score)))

train(*args, **kwargs)

Train the model, need to be overrided