MGB Framework

Titarl | Beginner guide

Overview

Titarl is a Data Mining algorithm designed to extract and use temporal rules from symbolic time series and time sequences (SSTS). Titarl rules can be directly interpreted (through the help of the Rule Viewer), used for predictions/detection, or used as input of other analysis. The Titarl binary also include code to automate the cross-validation evaluation of its rules as well as the implementation of various other Machine Learning algorithms (for comparison).

Titarl can learn rules such as:

These rules are *very* simple examples. Titarl can of course learn much more complex rules. Titarl rules can be use for forecasting (prediction in the future), detection (prediction in the past) or just raw correlation analysis.

Getting Titarl

Titarl is available on the download page.

Next, we invite you to read the Titarl's tutorial.

Need help?

In case of questions or problems, contact me at mathieug@andrew.cmu.edu.