Тип публикации: статья из журнала
Год издания: 2024
Идентификатор DOI: 10.1134/S1052618824700043
Ключевые слова: <i>k</i>-means algorithm, integrated circuits, clustering, James–Stein shrinkage estimator, heuristics, radioelectronic items, electrothermal preparation
Аннотация: A reduction in the James–Stein shrinkage estimator might significantly increase the accuracy of cluster analysis of <i>k</i>-means for a relatively broad range of data. The efficiency of using the James–Stein shrinkage estimator for automatically grouping industrial products in homogeneous production batches is considered. Tests arПоказать полностьюe conducted for batches of integrated circuits by comparing the shrinkage results with those obtained using the traditional <i>k-</i>means algorithm. The dataset is normalized according to the values of the acceptable drift, acceptable parameters, and standard deviation. As established using the Rand index, clustering is far more accurate in the automatic grouping of industrial products in homogeneous production batches, when average values of inconclusive parameters drop to zero. It is established that the reduction of the James–Stein shrinkage estimator decreases the influence of inconclusive parameters of standard data to acceptable values.
Журнал: Journal of Machinery Manufacture and Reliability
Выпуск журнала: Т.53, №3
Номера страниц: 254-262
ISSN журнала: 10526188
Место издания: Москва
Издатель: Allerton Press, Inc.