MV¶

class MV(answers, n_classes=2, sparse=False, **kwargs)¶

Majority voting¶

Most answered label per task

__init__(answers, n_classes=2, sparse=False, **kwargs)¶

Majority voting strategy: most answered label

\[\mathrm{MV}(i, \mathcal{D}) = \underset{k\in[K]}{\mathrm{argmax}} \sum_{j\in\mathcal{A}(x_i)}\mathbf{1}(y_i^{(j)} = k)\]

Parameters:

answers (dict) –

Dictionary of workers answers with format

{
    task0: {worker0: label, worker1: label},
    task1: {worker1: label}
}

sparse (bool, optional) – If the number of workers/tasks/label is large (\(>10^{6}\) for at least one), use sparse=True to run per task
n_classes (int, optional) – Number of possible classes, defaults to 2

get_answers()¶

Get labels obtained with majority voting aggregation

get_probas()¶

Get labels obtained with majority voting aggregation