Selecting binary classification algorithms
This section will be similar to the last; we’ll cover the high-level machine learning algorithms supported by ML.NET.
Our focus is not on the mathematics underlying these trainers but on their key differences and distinctions, and also on when you ought to consider using one versus another.
When I first learned the details of machine learning, one of the things that surprised me the most was how similar classification and regression tasks are.
In regression, you’re often trying to build a linear function that can calculate a value by multiplying your data columns by different weights, as we saw at the beginning of Chapter 8, Regression Experiments with ML.NET AutoML.
Classification works in very similar ways most of the time, where we determine a linear relationship between our data points and then calculate a value.
The difference with classification is that we usually don’t care about the exact value we...
