Let's quickly review supervised learning with an example. When you are training machine-learning algorithms, you are able to observe and direct the learning by providing labels. Think about the following dataset, where each row indicates a customer and each column represents a different feature such as Age, Gender, Income, Profession, Tenure and City. Take a look at this table:
You may want to perform different kinds of analysis. One of them could be to predict which of the customers is likely to leave, namely, churn analysis. To do that, you need to label each customer based on their history to indicate which customers have left or stayed, as displayed here, in this table:
Your algorithm will learn the characteristics of customers based on their label. Algorithm will learn the characteristics of customers who left or stayed, and, when...
