Bob 2.0 training of two GMMs for two types of features
Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.
Parameters allow users to change the configuration of an algorithm when scheduling an experiment
|number-of-gaussians||The number of Gaussian Components||uint32||100|
|maximum-number-of-iterations||The maximum number of iterations for the EM algorithm||uint32||10|
The code for this algorithm in Python
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Implements a GMM-based training, each GMM model for each of two types of data