A machine‐learning approach to detecting unknown bacterial serovars

Statistical Analysis and Data Mining

Ferit Akova²  V. Jo Davisson²  Bartek Rajwa³  Arun K. Bhunia⁴  E. Daniel Hirleman⁵  Murat Dundar⁵  J. Paul Robinson⁶ 

[1] Bindley Bioscience Center, Purdue University, W. Lafayette, IN 47907, USA;Department of Computer and Information Science, Indiana University‐Department of Food Science, Purdue University, W. Lafayette, IN 47907, USA;Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, W. Lafayette, IN 47907, USABindley Bioscience Center, Purdue University, W. Lafayette, IN 47907, USA;Purdue University, Indianapolis, IN 46202, USA;School of Mechanical Engineering, Purdue University, W. Lafayette, IN 47907, USA

关键词: nonexhaustive training data;    Bayesian classifier;    novelty detection;    anomaly detection;   

DOI  :  10.1002/sam.10085

学科分类：社会科学、人文和艺术（综合）

来源: John Wiley & Sons, Inc.

【 授权许可】

Unknown