SD metrics implements a GMM for probabilistic modelling of continuous static data. Held-out data (registered/synthetic/etc) can then be scored with a likelihood given the fit on the reference dataset.
A similar approach could be considered for temporal data with probabilistic models such as HMM.
SD metrics also implements so time series metrics.
SD metrics implements a GMM for probabilistic modelling of continuous static data. Held-out data (registered/synthetic/etc) can then be scored with a likelihood given the fit on the reference dataset.
A similar approach could be considered for temporal data with probabilistic models such as HMM.
SD metrics also implements so time series metrics.