Using AdaBoost to improve the performance of simple classifiers
Anvarjon Mahkamov, T.S. Jumayev, Dilmurod Tuhtanazarov, Alimjon Dadamuxamedov · 2023
The article presents the results of increasing recognition efficiency based on the solution of a model problem using an algorithm such as AdaBoost, which forms a “strong” classifier based on a combination of “weak” classifiers. Algorithm software has been developed with the help of which the data representing two classes of objects is classified. Recognition errors are graphically presented, and the advantages and disadvantages of this algorithm are described.