Anomaly Detection for Rules-Based System
For cheat likelihood calculation, a method records client activity for a client. The client activity includes components of a game economy including burns calculated as a function of measurable client sacrifices to a game and earns calculated as a function of measurable game rewards from the game. The method calculates the cheat likelihood from the probability of the client activity being anomalous.
Modeling Consumer Activity (Pending)
For modeling consumer activity, code generates potential model types. In addition, the code divides activity data into a training data set, a test data set, and a validation data set. The code further trains the potential model types with the training set data. In addition, the code selects a model type with the test data set. The code calculates algorithmic parameters with the validation data set.