Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
34th (2020)
Session ID : 4Rin1-37
Conference information

Clustering method for data with mixed parametric structures
*Kohei TAMURAKoutarou TAMURA
Author information
CONFERENCE PROCEEDINGS FREE ACCESS

Details
Abstract

Regarding the structural complexity of data, stratification of the data using a clustering method is important for constructing a model based on more detailed characteristics of the data. In particular, the data such as product failures shows there are various processes causing failures. This implies it is necessary to stratify the data for more precise analysis. However, these stratification factors are rarely acquired as data, and it is often difficult to grasp them. In this research, we propose a clustering method for extracting data structures that follow a Weibull distribution event occurrence data in a certain market product.

Content from these authors
© 2020 The Japanese Society for Artificial Intelligence
Previous article Next article
feedback
Top