Did HW4 - Q1a
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Uzair Mohammed
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hw4/bn.py
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hw4/bn.py
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# Defining the local conditional probability distributions
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P_F = {1: 0.01, 0: 0.99}
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P_E = {1: 0.02, 0: 0.98}
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P_A_given_FE = {(1, 1): 0.95, (1, 0): 0.94, (0, 1): 0.29, (0, 0): 0.001}
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P_B_given_A = {1: 0.90, 0: 0.05}
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P_C_given_A = {1: 0.70, 0: 0.01}
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# Function to calculate joint probabilities
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def joint_probability(f, e, a, b, c):
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return (P_F[f] * P_E[e] * P_A_given_FE[(f, e)] *
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P_B_given_A[a if b else 0] *
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P_C_given_A[a if c else 0])
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# Calculating total probabilities where B=1 and C=1 respectively
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total_P_B_1 = sum([joint_probability(f, e, a, b, c) for f in [1, 0] for e in [1, 0]
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for a in [1, 0] for b in [1, 0] for c in [1, 0]])
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total_P_C_1 = sum([joint_probability(f, e, a, b, c) for f in [1, 0] for e in [1, 0]
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for a in [1, 0] for b in [1, 0] for c in [1, 1]])
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# Calculate P(F=1 | B=1)
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P_F_given_B = total_P_B_1 / (total_P_B_1 + total_P_B_1)
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# Calculate P(F=1 | C=1)
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P_F_given_C = total_P_C_1 / (total_P_C_1 + total_P_C_1)
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# Print the results
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print(f"P(F=1 | B=1): {P_F_given_B:.6f}")
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print(f"P(F=1 | C=1): {P_F_given_C:.6f}")
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hw4/hw4.pdf
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hw4/hw4.pdf
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main.aux
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main.aux
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main.tex
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\subsection{Odds and Evens}
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See attached submission.py file
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\newpage
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\section{Homework 3}
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\subsection{Probability}
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P(\text{Accident} = 1 | \text{Traffic} = 1) \rightarrow P(A | T) = \frac{P(T | A) \cdot P(A)}{P(T)}
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$$
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\end{itemize}
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\newpage
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\section{Homework 4}
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\subsection{Inference in Bayesian Networks}
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\begin{itemize}
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\item[a - c. ] Refer to bn.py
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\item[d. ]
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\end{itemize}
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\end{document}
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