October 2017
Beginner to intermediate
270 pages
7h
English
Content preview from Machine Learning for Developers
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Getting an intuitive idea with Seaborn pairplot
A very good idea when starting worked on a problem is to get a graphical representation of all the possible variable combinations.
Seaborn’s pairplot function provides a complete graphical summary of all the variable pairs, represented as scatterplots, and a representation of the univariate distribution for the matrix diagonal.
Let’s look at how this plot type shows all the variables dependencies, and try to look for a linear relationship as a base to test our regression methods:
sns.pairplot(iris2, size=3.0)<seaborn.axisgrid.PairGrid at 0x7f8a2a30e828>
Pairplot of all the variables in the dataset. ...
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