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2024 International Conference on Information Technologies

Regularization Methods for Neural Network Models and Logistic Regression Models in the Problem of Classifying Industrial Products into Homogeneous Batches

Vladimir Nikolaevich Krutikov
Guzel Sharipzhanovna Shkaberina
Elena Mikhailovna Tovbis
Lev Alexandrovich Kazakovtsev
Department of Applied Mathematics, Kemerovo State University; Kemerovo
Reshetnev Siberian State University of Science and Technology, Krasnoyarsk
Russian Federation
e-mail: levk@bk.ru
Abstract:

In this paper the problem of automatic grouping of semiconductor devices by homogeneous production batches is investigated. Algorithms for training logistic regression and an artificial neural network with regularization in the problems of classification of industrial products into homogeneous production batches are proposed.

Key words:
mixed-type regularization
classification
logistic regression
artificial neural networks