Dichotomic Prediction of an Event using Non Deterministic Finite Automata
P. Punitha Ilayarani, S. Celine, Maria Dominic · 2019 International Conference on Computing, Power and Communication Technologies (GUCON) · 2019
Prophecy about an imminent event is called prediction. This prediction can be used to equip with preparedness to face an event and come out successful by making right decisions at right time. To automate this process many machine learning algorithms which can predict with varying degrees with each having its own uniqueness. This paper introduces one such novel technique for prediction. This new technique encompasses the knowledge of the domain experts into single formulae and translates that formula into a state transition diagram which will predict the outcome of an event when given with new test parameters of an event. The prediction of an event from this algorithm will be dichotomy in nature and the parameters can also be weighted and also to detect the significance of the model canonical correlation technique is implemented.