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lenskit.stochastic.StochasticTopNConfig#

classlenskit.stochastic.StochasticTopNConfig#

Configuration for StochasticTopNRanker.

n:int |None =None#: The number of items to select. -1 or None to return all scored items.

rng:lenskit.random.DerivableSeed =None#: Random number generator configuration.

transform:Literal['softmax','linear']|None ='softmax'#

Transformation to convert scores into ranking probabilities.

softmax: Use the softmax of the item scores as the selection probabilities.
linear: Linearly re-scale item scores to be selection probabilities. This equivalent to min-max scaling the scores, then re-scaling to sum to 1.
None: No transformation, except negative scores are clamped to (almost) zero. Not recommended unless your item scorer emits multinomial probabilities.

scale:float =1.0#: Scalar multiplier to apply to scores prior to transformation. This is equivalent to the \(\beta\) parameter for parameterized softmax transformation. Larger values will decrease the entropy of the sampled rankings.