pyppca
Probabilistic PCA which is applicable also on data with missing values. Missing value estimation is typically better than NIPALS but also slower to compute and uses more memory. A port to Python of the implementation by Jakob Verbeek.
Usage:
from pyppca import ppca
C, ss, M, X, Ye = ppca(Y,d,dia)
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Release files for pyppca 0.0.4
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Source distribution (sdist)
| File | Size | Uploaded | |
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| pyppca-0.0.4.tar.gz | 2.8 kB | Details |
Release files / pyppca-0.0.4.tar.gz
| Download URL | pyppca-0.0.4.tar.gz |
|---|---|
| Size | 2.8 kB |
| Tags | Source |
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