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.
# Import the function from mvlearn.plotting import quick_visualize from mvlearn.datasets import load_UCImultifeature import matplotlib.pyplot as plt %matplotlib inline
# Load 4-class data Xs, y = load_UCImultifeature(select_labeled=[0,1,2,3])
# Quickly visualize the data quick_visualize(Xs, figsize=(5,5))
If we have class labels that we want to visualize too, we can easily add those¶
quick_visualize(Xs, labels=y, title='Labeled Classes', figsize=(5,5))