Anomaly Detection with the BigML Dashboard

9.3 Category

A category, taken from the dataset used to create it, is associated with each anomaly. Categories are useful to classify anomalies according to the domain which your data comes from. This is useful when you use BigML to solve problems across industries or multiple customers.

An anomaly category must be one of the 24 categories listed in Table 9.1 .

Table 9.1 Categories used to classify anomalies by BigML

Category

Aerospace and Defense

Automotive, Engineering and Manufacturing

Banking and Finance

Chemical and Pharmaceutical

Consumer and Retail

Demographics and Surveys

Energy, Oil and Gas

Fraud and Crime

Healthcare

Higher Education and Scientific Research

Human Resources and Psychology

Insurance

Law and Order

Media, Marketing and Advertising

Miscellaneous

Physical, Earth and Life Sciences

Professional Services

Public Sector and Nonprofit

Sports and Games

Technology and Communications

Transportation and Logistics

Travel and Leisure

Uncategorized

Utilities