| 摘要 |
Bayesian principal component analysis. In one embodiment, a computer-implemented method for performing Bayesian PCA including inputting a data model; receiving a prior distribution of the data model; determining a posterior distribution; generating output data based on the posterior distribution (such as, a data model, a plurality of principal components, and/or a distribution); and, outputting the output data. In another embodiment, a computer-implemented method including inputting a mixture of a plurality of data spaces; determining a maximum number of principal components for each of the data spaces within the mixture; and, outputting the maximum number of principal components for each of the data spaces within the mixture.
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