data mining algorithms

In recent years, data mining and machine learning methods in the medical field have received much attention and have optimized many complex issues in the medical field. One of the problems facing researchers is the appropriate dataset, and the suitable dataset on which different methods of data mining and machine learning can be applied is rarely found. One of the most reliable and appropriate datasets in the field of diabetes diagnosis is the Indian Survey Database. In this article, we have tried to review the methods that have been implemented in recent years using machine learning classification algorithms on this data set and compare these methods in terms of evaluation criteria and feature selection methods. After comparing these methods, it was found that models that used feature selection methods were more accurate than other approaches.

The emergence of mobile applications is forcing ambitious companies hoping to build loyalty for customers’ brands to rush towards marketing their brand applications. The present research was conducted with the aim of classifying loyal customers and measuring their loyalty level using data mining algorithms. The present research method is based on applied-descriptive and the statistical population included the customers of Asan Pardakht Company which were considered number ten thousand people and with the number of 700,000 transactions. These customers were separated by clustering operation and classified for performing different tests. By using the data of Fintech customers of Asan Pardakht Company, it was attempted by using the decision tree algorithm, in addition, to identifying active customers, to implement this algorithm, a way is made in order to increase customer loyalty and ultimately increase their profitability and create satisfaction among managers. In the present research, by implementing the different stages of Crisp methodology, clustering and testing different artificial intelligence algorithms, the most useful algorithm in order to identify the best customers and also to make them loyal and policies and implementable programs to be formulated in order to increase the satisfaction percentage and finally customers’ loyalty was explained and mentioned.