References of "Loos, Benjamin Laurent 0140854458"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailFlexible State-Merging for learning (P)DFAs in Python
Hammerschmidt, Christian UL; Loos, Benjamin Laurent UL; Verwer, Sicco et al

Scientific Conference (2016, October)

We present a Python package for learning (non-)probabilistic deterministic finite state automata and provide heuristics in the red-blue framework. As our package is built along the API of the popular ... [more ▼]

We present a Python package for learning (non-)probabilistic deterministic finite state automata and provide heuristics in the red-blue framework. As our package is built along the API of the popular \texttt{scikit-learn} package, it is easy to use and new learning methods are easy to add. It provides PDFA learning as an additional tool for sequence prediction or classification to data scientists, without the need to understand the algorithm itself but rather the limitations of PDFA as a model. With applications of automata learning in diverse fields such as network traffic analysis, software engineering and biology, a stratified package opens opportunities for practitioners. [less ▲]

Detailed reference viewed: 115 (10 UL)