You work for a retail company, and your task is to develop a model for predicting whether a customer will make a purchase on a given day. Your team has processed the company's sales data and created a table with specific columns, including customer ID, product ID, date, days since the last purchase, average purchase frequency, and a binary class indicating whether the customer made a purchase on the date in question. Your objective is to interpret the results of your model for individual predictions. What is the recommended approach?