print('\nProb for mammogram given NO cancer', 'P(M|C=no)', mamm_g_no_cancer.asPct(), sep='\n') # conditional probability table mammograms = Lea.buildCPT((cancer == 'yes', mamm_g_cancer), (cancer == 'no', mamm_g_no_cancer)) print('\nMammograms', 'P(M)', mammograms.asPct(), sep='\n') # get joint probs for all events joint_probs = Lea.cprod(mammograms, cancer) print('\nJoint Probabilities', 'P(M, C)', joint_probs.asPct(), sep='\n') # prob cancer GIVEN mammogram==pos print('\nThe Answer', 'P(C|M=pos)', cancer.given(mammograms == 'pos').asPct(), sep='\n') # prob cancer GIVEN mammogram==neg print('\nExtra Info', 'P(C|M=neg)',
print('Scenario 1', scenario1, sep='\n') # construct Scenario 2 scenario2 = Lea.buildCPT((coin == 'H', die6), (coin == 'T', die4)) print('Scenario 2', scenario2, sep='\n') # get joint probs for all events # -- scenario 1 joint_prob1 = Lea.cprod(coin, scenario1) print('Scenario 1', '* Joint Probabilities', joint_prob1, sep='\n') # get joint probs for all events # -- scenario 2 joint_prob2 = Lea.cprod(coin, scenario2) print('Scenario 2', '* Joint Probabilities', joint_prob2, sep='\n')
# prob for mamm given cancer == no mamm_g_no_cancer = Lea.fromValFreqs(('pos', 96), ('neg', 1000 - 96)) print('\nProb for mammogram given NO cancer', 'P(M|C=no)', mamm_g_no_cancer.asPct(), sep='\n') # conditional probability table mammograms = Lea.buildCPT((cancer == 'yes', mamm_g_cancer), (cancer == 'no', mamm_g_no_cancer)) print('\nMammograms', 'P(M)', mammograms.asPct(), sep='\n') # get joint probs for all events joint_probs = Lea.cprod(mammograms, cancer) print('\nJoint Probabilities', 'P(M, C)', joint_probs.asPct(), sep='\n') # prob cancer GIVEN mammogram==pos print('\nThe Answer', 'P(C|M=pos)', cancer.given(mammograms == 'pos').asPct(), sep='\n') # prob cancer GIVEN mammogram==neg print('\nExtra Info', 'P(C|M=neg)', cancer.given(mammograms == 'neg').asPct(), sep='\n')