pdstools.infinity.resources.prediction_studio.v24_2.prediction._sync

Classes

Prediction

The Prediction class provide functionality including retrieving

Module Contents

class Prediction(client, *, predictionId: str, label: str, status: str, lastUpdateTime: str, objective: str | None = None, subject: str | None = None)

Bases: pdstools.infinity.resources.prediction_studio.v24_2.prediction._mixin._PredictionV24_2Mixin, pdstools.infinity.resources.prediction_studio.v24_1.prediction.Prediction

The Prediction class provide functionality including retrieving notifications, models, adding conditional models, getting champion challengers, metrics, and plotting metrics.

Parameters:

  • predictionId (str)

  • label (str)

  • status (str)

  • lastUpdateTime (str)

  • objective (str | None)

  • subject (str | None)

get_notifications(category: pdstools.infinity.resources.prediction_studio.types.NotificationCategory | None = None, return_df: Literal[False] = False) → pdstools.infinity.internal._pagination.PaginatedList[pdstools.infinity.resources.prediction_studio.base.Notification]
get_notifications(category: pdstools.infinity.resources.prediction_studio.types.NotificationCategory | None = None, return_df: Literal[True] = True) → polars.DataFrame

Fetches a list of notifications for a specific prediction.

This function retrieves notifications related to a prediction. You can filter these notifications by their category. Optionally, the notifications can be returned as a DataFrame for easier analysis and visualization.

Parameters:

  • category ({"All", "Responses", "Performance", "Model approval", "Output", "Predictors", "Prediction deployment", "Generic"} or None) – The category of notifications to retrieve. If not specified, all notifications are fetched.

  • return_df (bool, default False) – If True, returns the notifications as a DataFrame. Otherwise, returns a list.

Returns:

A list of notifications or a DataFrame containing the notifications, depending on the value of return_df.

Return type:

PaginatedList[Notification] or polars.DataFrame

get_champion_challengers()

Fetches list of ChampionChallenger objects linked to the prediction.

This function fetches Champion-challenger pairs from a prediction. In cases where a challenger model is absent, it returns a ChampionChallenger object containing only the champion model.

Returns:

A list of entries, each pairing a primary model with its challenger across various segments of the prediction.

Return type:

list of ChampionChallenger

add_conditional_model(new_model, category: str, context: str | None = None)

Incorporates a new model into a prediction for a specified category and context.

Parameters:

  • new_model (str or Model) – Identifier of the model to be added.

  • category (str) – The category under which the model will be classified.

  • context (str, optional) – The specific context or scenario in which the model will be utilized.

Returns:

An object detailing the updated configuration with the newly added model.

Return type:

ChampionChallenger