Fix incorrect probabilities and typos

week6/solution/exercise1-2.py

@@ -45,7 +45,7 @@ houses = ['gryffindor', 'ravenclaw', 'slytherin', 'hufflepuff']
 for i, prob in enumerate([0.002, 0.002, 0.0001, 0.01]):
     pd['PureHeart=true|House={0}'.format(houses[i])] = prob
     pd['PureHeart=false|House={0}'.format(houses[i])] = 1 - prob
-for i, prob in enumerate([0.05, 0.02, 0.02, 0.001]):
+for i, prob in enumerate([0.05, 0.02, 0.02, 0.01]):
     pd['Brave=true|House={0}'.format(houses[i])] = prob
     pd['Brave=false|House={0}'.format(houses[i])] = 1 - prob
 for house in houses:

week6/solution/exercise3.py

@@ -61,8 +61,8 @@ brave_cpd = TabularCPD(
     evidence=['House'],
     evidence_card=[4],
     values=[
-        [0.05, 0.02, 0.02, 0.001], # Brave true
-        [1 - 0.05, 1 - 0.02, 1 - 0.02, 1 - 0.001] # Brave false
+        [0.05, 0.02, 0.02, 0.01], # Brave true
+        [1 - 0.05, 1 - 0.02, 1 - 0.02, 1 - 0.01] # Brave false
     ]
 )
 hogwarts_bn.add_cpds(brave_cpd)

week6/solution/exercise5.py

@@ -12,10 +12,10 @@ hogwarts_hmm = DenseHMM()
 states = ['gryffindor', 'ravenclaw', 'slytherin', 'hufflepuff']
 
 # Possible observations: 
-# 0. AcromantulaSighting=true, UnicornSighting=true (AU)
-# 1. AcromantulaSighting=true, UnicornSighting=false (AX)
-# 2. AcromantulaSighting=false, UnicornSighting=true (XU)
-# 4. AcromantulaSighting=false, UnicornSighting=false (XX)
+# 0. AcromantulaSighting=true, UnicornSighting=true (XX)
+# 1. AcromantulaSighting=true, UnicornSighting=false (XO)
+# 2. AcromantulaSighting=false, UnicornSighting=true (OX)
+# 4. AcromantulaSighting=false, UnicornSighting=false (OO)
 
 # emission probability distributions for the two hidden states
 state_dists = [None, None, None, None]
@@ -24,7 +24,6 @@ for i, house in enumerate(states):
     query = inference.query(variables=['AcromantulaSighting','UnicornSighting'], evidence={'House': i, 'TimeOfDay': 1} )
     val = query.values
     probabilities = [val[0,0], val[0,1], val[1,0], val[1,1]]
-    print(np.array(probabilities).sum())
     cur_state_dist = Categorical([probabilities])
     state_dists[i] = cur_state_dist