Training models in Optimus
Now that we know how the test/train, split, and cross-validation processes work, let me tell you something amazing. You don't have to struggle with configuring and writing code to make this process work, as Optimus will do the heavy lifting for you.
Let's see the ML models available in Optimus.
Linear regression
Linear regression is a supervised ML algorithm that is useful for finding out how variables are linked to each other. By assigning a linear equation to the data that we have, we can use fresh data and predict the output, as illustrated in the following diagram:
Figure 8.4 – A line approximated to a cluster of points
In the preceding diagram, we can see a line that approximates a cluster of points. Let's see how to calculate this approximation.
First, let's start by creating a dataset with the following code:
import numpy as np
size = 10000
data = {&...
