pdstools.infinity.resources.prediction_studio.v24_2.champion_challenger._sync¶

Classes¶

ChampionChallenger

The ChampionChallenger class manages champion and challenger models

Module Contents¶

class ChampionChallenger(client, prediction_id: str, active_model, cc_id: str | None = None, context: str | None = None, category: str | None = None, challenger_model=None, champion_percentage: float | None = None, model_objective: str | None = None)¶

Bases: pdstools.infinity.resources.prediction_studio.v24_2.champion_challenger._mixin._ChampionChallengerV24_2Mixin, pdstools.infinity.resources.prediction_studio.base.ChampionChallenger

The ChampionChallenger class manages champion and challenger models within a prediction context. It provides functionalities for:

Refreshing champion challenger data
Deleting challenger models
Promoting challenger models
Updating challenger response percentages
Adding new models
Cloning an ADM active model
Adding/removing predictors

Parameters:

prediction_id (str)
cc_id (str | None)
context (str | None)
category (str | None)
champion_percentage (float | None)
model_objective (str | None)

client¶

The client used to interact with the API.

Type:: Client

prediction_id¶

The ID of the prediction.

Type:: str

active_model¶

The active model in the prediction.

Type:: Model

cc_id¶

The ID of the champion challenger.

Type:: str | None

context¶

The context of the prediction.

Type:: str | None

category¶

The category of the prediction.

Type:: str | None

challenger_model¶

The challenger model.

Type:: Model | None

champion_percentage¶

The percentage of responses attributed to the champion model.

Type:: float | None

model_objective¶

The objective of the model.

Type:: str | None

list_available_models_to_add(return_df: bool = False) → pdstools.infinity.internal._pagination.PaginatedList | polars.DataFrame¶

Fetches a list of models eligible to be challengers.

Queries for models that can be added as challengers to the current prediction for the current active model. Offers the option to return the results in a DataFrame format for easier data handling.

Parameters:: return_df (bool, optional) – Determines the format of the returned data: a DataFrame if True, otherwise a list of model instances. Defaults to False.
Returns:: A list of model instances or a DataFrame of models, based on the return_df parameter choice.
Return type:: PaginatedList[Model] or pl.DataFrame