A study on Bayesian Network-K2 Algorithm

The basis of the Bayesian networks is the graphical representation of the arrows and nodes which represent relationships between variables. Random variables that take parent and child names according to the direction of the arrows and conditional and marginal probabilities of these random variables provide great convenience to the researcher in calculating the likelihood of a desired event. Bayesian networks can be created in two ways: "Causal Bayesian Networks" and "Algorithm Based Bayesian Networks". Both methods have advantages within themselves and vary according to the research topic. There are many different algorithms that are used when networking. One of these algorithms is the K2 algorithm. In this work, it is explained how to construct Causal Bayesian Networks and Algorithm Based Bayesian Networks on one example for each