Market basket analysis developed on the refrigerator control system with machine learning algorithms In data mining applications

The purpose of this study was to analyze the basket basket developed by using machine mining algorithms by using data mining data. Another objective of this study is to find out the critical level in the system by developing a refrigerator control system software application and algorithm using forecasting modeling and machine learning method; and the estimated frequency of consumption. An internet-based simulated application software, written in Visual Studio C#, was developed to interpret data and display the results on the web. The rules of association have been applied to the application software and the data in the database. The data in the refrigerator can be accessed from any location by mobile phone and the current situation can be learned. In this study, it is aimed to develop a model from the data whose results are known with the application developed with the predictive model of data mining models and to estimate the result values for the data sets whose results are unknown. In market basket analysis and association rule; It is aimed to determine the buying habits of customers by finding association-relationship ties between the products that customers purchase during shopping.