Beispiel #1
0
 def entropy_gain(self, action, data=None):
     return entropy_gains.theory_entropy_gain(action, data)
Beispiel #2
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	def entropy_gain(self, action, data=None):
		return entropy_gains.theory_entropy_gain(action, data)
Beispiel #3
0
import newmodel
import learners
import entropy_gains
import world
import Datapoint
import test_data


dcol=test_data.dat_col

rl=learners.RandomLearner()
print entropy_gains.theory_entropy_gain(rl.choose_action(dcol))

tl=learners.TheoryLearner()
#print tl.choose_action(dcol)

print entropy_gains.theory_entropy_gain(((0,0),(2,0)))
#print entropy_gains.theory_entropy_gain(tl.choose_action(dcol))


# import test_data
# d0=test_data.dat_col[0]
# #print 'oh! ', newmodel.p_data_hypothesis([d0], 0, (0,0))
# print 'oh! ', newmodel.p_singledata_hypothesis(d0, 2, (0,0))
# d0.display()

# suma=0
# count=0
# for m in world.machines:
# 	for t in world.available_toys: