Editing Anomaly detection


Outlier / Anomaly detection

== Anomaly detection of numeric data ==
* Median
* Range Checks
* All values is event
* The values are the same even the column is totally different

== Anomaly detection of categorical data (qualitative variable) ==
* Normal distribution e.g. The interest of audiences should be very different NOT coherent

== Anomaly detection for time series data ==
* Trend
* Dramatically Increase or decrease of rows count for each time period

== Anomaly detection for stirng data ==

* created time of the text message
* time frequency of the text message
* length of the text message

More on: [https://en.wikipedia.org/wiki/Outlier#Identifying_outliers Outlier - Wikipedia]

[[Category:Data_hygiene]]
[[Category:Data Science]]