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%matplotlib inline
The downside to using dimensionality reduction to visualize your data is that
some variance will likely be removed. To help get a sense for the integrity of your low
dimensional visualizations, we built the describe
function, which computes
the covariance (samples by samples) of both the raw and reduced datasets, and
plots their correlation.
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# Code source: Andrew Heusser
# License: MIT
# import
import hypertools as hyp
import numpy as np
# load example data
geo = hyp.load('weights_sample')
data = geo.get_data()
# plot
hyp.describe(data)