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In this work, we study the use of logistic regression in manufacturingfailures detection. As a data set for the analysis, we used the data fromKaggle competition Bosch Production Line Performance. We considered the use ofmachine learning, linear and Bayesian models. For machine learning approach, weanalyzed XGBoost tree based classifier to obtain high scored classification.Using the generalized linear model for logistic regression makes it possible toanalyze the influence of the factors under study. The Bayesian approach forlogistic regression gives the statistical distribution for the parameters ofthe model. It can be useful in the probabilistic analysis, e.g. riskassessment.

Machine Learning, Linear and Bayesian Models for Logistic Regression in Failure Detection Problems