[FIXED] Visualizing Prediction and Test values for comparison

Issue

I'd like to make comparing this Prediction and Test values easier, so I'm thinking two ways to achieve that:

1. Scale the X and Y axis to the same scale
2. Plot a linear line (y=x)
3. Really like to have some way to either 'exclude' the outliers or perhaps 'zoom in' to the area where the points are dense, without manually excluding the outliers from the dataset (so its done automatically). Is this possible?

sns.scatterplot(y_pred, y_true)
plt.grid()

Looked around and tested plt.axis('equal') as mentioned on another question but it didn't seem quite right. Tried using plt.plot((0,0), (30,30)) to create the linear plot but it didn't show anything. Any other input on how to visualise this would be really appreciated as well. Thanks!

Solution

There are short ways to achieve everything you've suggested:

1. Force scaled axes with matplotlib.axes.Axes.set_aspect.
2. Add an infinite line with slope 1 through he origin with matplotlib.axes.Axes.axline
3. Set your plot to interactive mode, so you can pan and zoom. The way to do this depends on your environment and is explained in the docs.

Best to combine them all.

import matplotlib.pyplot as plt
from numpy import random

plt.ion()  # activates interactive mode in most environments
plt.scatter(random.random_sample(10), random.random_sample(10))
ax = plt.gca()
ax.axline((0, 0), slope=1)
ax.set_aspect('equal', adjustable='datalim')  # force equal aspect

Answered By - Joooeey