Exercise - Train and evaluate a classification model

Classification is a form of supervised machine learning in which you train a model to use the features (the x values in our function) to predict a label (y) that calculates the probability of the observed case belonging to each of a number of possible classes, and predicting an appropriate label. The simplest form of classification is binary classification, in which the label is 0 or 1, representing one of two classes; for example, "True" or "False"; "Internal" or "External"; "Profitable" or "Non-Profitable"; and so on.

In this exercise, you will train and evaluate a classification model.

This exercise requires the use of the Microsoft Learn sandbox to complete. You can access the exercise from the link below.

Exercise Link

Exercise - Train and evaluate a classification model