Bayesian Networks using PgmPy
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Probability and Bayesian Theory Continue
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Description: # Probability and Bayesian Theory ## Additive and Multiplicative Rules of Probability Consider $A$,$B$ are two events, and $P$ denotes the probability of occurence of an event.
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Bayesian Networks Continue
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Description: # Bayesian Networks
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Features of a Bayesian Network Continue
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Description: # Features of a Bayesian Network So far we have seen that: * A Bayesian Network is a joint probability distribution of a set of random variables.
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Fraud Modeling Example with pgmpy Continue
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Description: # Fraud Modeling Example with pgmpy pgmpy is one of the popular packages to do Bayesian Network modeling. We shall continue to use the fraud modeling example to visualize our network. pgmpy is good for simpler problems, to visualize the indepencies and CPDs. It doesn't work very well for large dimensional problems. There are other toolkits which are available such as: * WINMINE by Microsoft: https://www.microsoft.com/en-us/research/project/winmine-toolkit/
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Credit Approval Model using a Bayesian Network Continue
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Description: # Credit Approval Model using a Bayesian Network Let us look at a credit approval process example. Please note that the model/process shown here does not closely follow any real life approval process. This model is a completely generated from scratch solely for the purpose of practice and easy explanation. There are two factors, Outstanding Loan (OL) and Payment History (PH) which are independent of each other and influence another factor Credit Rating (CR). Credit Rating and Income Level (IL) are in turn two independent factors which influence Interest Rate (IR) of a credit line that would be extended to a customer. Depending upon CR and IL, a customer may receive a credit/loan at a premium rate, par rate or discounted interest rate.
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