Timeline for Doing PCA with $m$ vectors in $d$ dimensions and then plotting only $n$ vectors, when $n<d<m$
Current License: CC BY-SA 3.0
5 events
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| Apr 13, 2017 at 12:44 | history | edited | CommunityBot |
replaced http://stats.stackexchange.com/ with https://stats.stackexchange.com/
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| Jan 30, 2017 at 17:38 | comment | added | z80crew |
Great! I used sample = numpy.array( [data[i] for i in random.sample(range(len(data)), 10000)] ) to generate a subset of 10,000 vectors. Then pca = PCA(sample) to do the PCA transformation. And at last [pca.project(d) for d in data] to project the original vectors according to the transformed coordinates.
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| Jan 30, 2017 at 17:33 | vote | accept | z80crew | ||
| Jan 30, 2017 at 14:49 | review | First posts | |||
| Jan 30, 2017 at 15:08 | |||||
| Jan 30, 2017 at 14:48 | history | answered | Conrad De Peuter | CC BY-SA 3.0 |