In this section, we explore some Python libraries to build our decision system. I focus on Bayesian and fuzzy logic models for implementing the decision system.

We can implement Bayesian probability using Python. For our demo, we generate output values from two independent variables, *x _{1}* and

*c* is a random value. We define α, β_{1}, β_{2}, and σ as 0.5, 1, 2.5, and 0.5.

These independent variables are generated using a random object from the NumPy library. After that, we compute the model with these variables.

We can implement this case with the following scripts: ...

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