crowdkit.aggregation.classification.wawa.Wawa
| Source code
Wawa(self)
The Worker Agreement with Aggregate (Wawa) algorithm consists of three steps:
Parameters | Type | Description |
---|---|---|
labels_ | Optional[Series] | The task labels. The |
skills_ | Optional[Series] | The workers' skills. The |
probas_ | Optional[DataFrame] | The probability distributions of task labels. The |
Examples:
from crowdkit.aggregation import Wawafrom crowdkit.datasets import load_datasetdf, gt = load_dataset('relevance-2')result = Wawa().fit_predict(df)
Method | Description |
---|---|
fit | Fits the model to the training data. |
fit_predict | Fits the model to the training data and returns the aggregated results. |
fit_predict_proba | Fits the model to the training data and returns probability distributions of labels for each task. |
predict | Predicts the true labels of tasks when the model is fitted. |
predict_proba | Returns probability distributions of labels for each task when the model is fitted. |
Last updated: March 31, 2023