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Title:Improving Diagnosis Efficiency via Machine Learning
Conference:ITC 2018
Tags:chain failure, Diagnosis, diagnosis outcome, diagnosis success, Fail log, fail pattern, feature importance, gini impurity, hyper parameter, imbalanced data, Machine Learning, prediction performance, random forest, scan chain, scan chain failure and yield learning
Abstract:
Based on features extracted from fail logs, machine learning methods are used to predict diagnostic information without running time-consuming diagnosis. Experiments on various fail logs demonstrate the efficacy of the concept.
Improving Diagnosis Efficiency via Machine Learning
Improving Diagnosis Efficiency via Machine Learning
