DATA DESCRIPTION:

Machine learning project to predict pass/fail yield in semiconductor manufacturing using sensor data with 591 features. Focus on building accurate classifiers and identifying key features to improve process monitoring and reduce costs. The dataset presented in this case represents a selection of such features where each example represents a single production entity with associated measured features and the labels represent a simple pass/fail yield for in house line testing. Target column “ –1” corresponds to a pass and “1” corresponds to a fail and the data time stamp is for that specific test point.