A Random Forest Based Classifier for Error Prediction of Highly Individualized Products

Autor:	Gerd Groner
Rok vydání:	2018
Předmět:	Development environment business.industry Computer science Artificial intelligence Machine learning computer.software_genre business Imbalanced data computer Classifier (UML) Random forest
Zdroj:	Machine Learning for Cyber Physical Systems ISBN: 9783662584842 ML4CPS
DOI:	10.1007/978-3-662-58485-9_4
Popis:	This paper presents an application of a random forest based classifier that aims at recognizing flawed products in a highly automated production environment. Within the course of this paper, some data set and application features are highlighted that make the underlying classification problem rather complex and hinders the usage of machine learning algorithms straight out-of-the-box. The findings regarding these features and how to treat the concluded challenges are highlighted in a abstracted and generalized manner.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c99bda3361fc57f4665948b925fc465f https://doi.org/10.1007/978-3-662-58485-9_4 Zobrazit plný text záznamu