prepare_binned_classification_data_times()

Prepare binned, time-dependent classification data.

Usage

Source

prepare_binned_classification_data_times(
    probs,
    reals,
    times,
    fixed_time_horizons,
    heuristics_sets=[{"censoring_heuristic": "adjusted", "competing_heuristic": "adjusted_as_negative"}],
    stratified_by=("probability_threshold",),
    by=0.01,
    risk_set_scope=["pooled_by_cutoff", "within_stratum"]
)

This function constructs the foundational binned data needed for time-to-event performance analysis. It bins predictions by probability thresholds, applies censoring and competing event heuristics, and stratifies the data across specified time horizons. The output is a detailed breakdown of outcomes within each bin, which can be used for calibration or passed to prepare_performance_data_times for full performance metric calculation.

Parameters

probs: Dict[str, np.ndarray]

A dictionary mapping model or dataset names (str) to their predicted probabilities.

reals: Union[np.ndarray, Dict[str, np.ndarray]]

The true event statuses (e.g., 0=censored, 1=event, 2=competing).

times: Union[np.ndarray, Dict[str, np.ndarray]]

The event or censoring times.

fixed_time_horizons: list[float]

A list of numeric time points for performance evaluation. Integer inputs are accepted and normalized to floats.

heuristics_sets: list[Dict] = [{"censoring_heuristic": "adjusted", "competing_heuristic": "adjusted_as_negative"}]


Specifies how to handle censored data and competing events.

stratified_by: Sequence[str] = ("probability_threshold",)


Variables for stratification. Defaults to ("probability_threshold",).

by: float = 0.01

The step size for probability thresholds. Defaults to 0.01.

risk_set_scope: Sequence[str] = ["pooled_by_cutoff", "within_stratum"]


Defines the scope for risk set calculations. Defaults to ["pooled_by_cutoff", "within_stratum"].

Returns

pl.DataFrame

A Polars DataFrame with binned, time-dependent data. Each row represents a unique combination of dataset, bin, time horizon, heuristic, and other strata.