Associative rules as "if… then" are used to solve a market basket analysis task.
Every purchase is named as a "transaction". Research of client's behavior is created based on big set of such transactions.
Oracle Data Miner was used in this project.
This is Oracle SQL Developer extension, which lets data analysts to look through their data, create and estimate several models of machine learning and accelerate deployment of models.
Thanks to this technology users can work directly with the data, which is in data base.
There is an opportunity for data analysts to explore the data with the help of graphs, create and describe forecast models. In the course of working process user's analytical methodology is collected and documented. It can be kept for opportunity of joint use.
As a result, data, received with the help market basket analysis, lets optimize range of goods and stock, their placement in sale rooms and increase sales volume due to offering of concomitant goods to clients.