Data Mining Algorithms for Solving Classification Problems

Abstract

The purpose of the work is to study the data mining existing approaches to solve the forecasting situations in oil wells problem based on their work parameters accumulated values. The various algorithms functioning were analyzed. From the data presented, it can be seen that the greatest number of correct and accurate classifications of situations is obtained using the machine learning method support vector machine. This algorithm can be used as a basic algorithm for modification in the case of multiple classification in further studies. This program will help the engineer to intervene in the production process in time and prevent high production costs.