Function max_PI

modAL/acquisition.py:105–122

Maximum PI query strategy. Selects the instance with highest probability of improvement. Args: optimizer: The :class:`~modAL.models.BayesianOptimizer` object for which the utility is to be calculated. X: The samples for which the probability of improvement is to be calculat

(optimizer: BaseLearner, X: modALinput, tradeoff: float = 0,
           n_instances: int = 1)

def max_PI(optimizer: BaseLearner, X: modALinput, tradeoff: float = 0,
           n_instances: int = 1) -> np.ndarray:
    """
    Maximum PI query strategy. Selects the instance with highest probability of improvement.

    Args:
        optimizer: The :class:`~modAL.models.BayesianOptimizer` object for which the utility is to be calculated.
        X: The samples for which the probability of improvement is to be calculated.
        tradeoff: Value controlling the tradeoff parameter.
        n_instances: Number of samples to be queried.

    Returns:
        The indices of the instances from X chosen to be labelled.
        The pi metric of the chosen instances.

    """
    pi = optimizer_PI(optimizer, X, tradeoff=tradeoff)
    return multi_argmax(pi, n_instances=n_instances)


def max_EI(optimizer: BaseLearner, X: modALinput, tradeoff: float = 0,