A comparative evaluation of outlier detection algorithms: Experiments and analyses.

•Experimental comparison and analysis of unsupervised outlier detection techniques.•Based on ROC, precision-recall, computation time, memory usage and robustness.•Extend a nonparametric Bayesian method to model numerical and categorical features.•Experiments make use of novel industrial datasets and assess generalization abilities.