Machine LEARNING-XV. Anomaly Detection anomaly Detection (Week 9)

http://blog.csdn.net/pipisorry/article/details/44783647

Machine learning machines Learning-andrew NG Courses Study notes

Anomaly Detection anomaly Detection

The motive of problem motivation problem

Anomaly Detection Example

Applycation of anomaly Detection

Note: for frauddetection: The users behavior examples of features of a users activity is on the Website it ' d be things like,maybe X1 was how often does this user log in, x2,the number of what pages visited, or the Numbe R of transactions, maybe X3 is the number of posts of the users on the forum, feature X4 could being the typing speed of the User. And so your can model p of x based on this sort of data.

Gaussian Distribution Gaussian distribution

Algorithm algorithm

Developing and evaluating an Anomaly Detection system developing and evaluating anomaly detection systems

Anomaly Detection vs. supervised learning anomaly detection vs. supervised learning

Choosing what do Features to use choose which Features

Gaussian distribution of multivariate Gaussian distribution (Optional) multivariable

Anomaly Detection using the multivariate Gaussian distribution (Optional) anomaly detection with multi-variable Gaussian distribution

from:http://blog.csdn.net/pipisorry/article/details/44783647

Machine LEARNING-XV. Anomaly Detection anomaly Detection (Week 9)