Model returned by the learning algorithm.
Model returned by the learning algorithm.
0.2.0
Apply the IBCC Algorithm.
Apply the IBCC Algorithm.
The dataset (spark dataset of types.RealAnnotation)
Iterations of the learning algorithm
Minimum MSE for the algorithm to continue iterating
0.2.0
Provides functions for transforming an annotation dataset into a standard label dataset using the PM algorithm.
This algorithm only works with continuous target variables. Thus you need an annotation dataset of types.RealAnnotation:
The algorithm returns a PM.PMModel, with information about the class true label estimation and the annotators weight
0.2.0
Q. Li, Y. Li, J. Gao, B. Zhao, W. Fan, and J. Han. Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation. In SIGMOD, pages 1187–1198, 2014.