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Using quick_visualize() to quickly understand multi-view data

Easily view and understand underlying clusters in multi-view data

As a simple example, say we had high-dimensional multi-view data that we wanted to quickly visualize before we begin our analysis. With quick_visualize, we can easily do this. As an example, we will visualize the UCI Multiple Features dataset.

[1]:
# Import the function
from mvlearn.plotting import quick_visualize
from mvlearn.datasets import load_UCImultifeature

import matplotlib.pyplot as plt
%matplotlib inline
[2]:
# Load 4-class data
Xs, y = load_UCImultifeature(select_labeled=[0,1,2,3])
[3]:
# Quickly visualize the data
quick_visualize(Xs, figsize=(5,5))
../../_images/tutorials_plotting_quick_visualize_tutorial_4_0.png

If we have class labels that we want to visualize too, we can easily add those

[4]:
quick_visualize(Xs, labels=y, title='Labeled Classes', figsize=(5,5))
../../_images/tutorials_plotting_quick_visualize_tutorial_6_0.png