I’d be a lot more inclined to respond to this if I didn’t need to calculate probability values (ie. could input weights instead, which were then normalized.)
To that end, here is a simple Python script which normalizes a list of weights (given as commandline arguments) into a list of probabilities:
#!/usr/bin/python
import sys
weights = [float(v) for v in sys.argv[1:]]
total_w = sum(weights)
probs = [v / total_w for v in weights]
print ('Probabilities : %s' % (", ".join([str(v) for v in probs])))
Useful script, but I’m not sure it’s necessary for this question. These aren’t exclusive or compared to each other. Each probability is independent, “likelihood that this topic will fit into lesswrong expectations”.
I’d be a lot more inclined to respond to this if I didn’t need to calculate probability values (ie. could input weights instead, which were then normalized.)
To that end, here is a simple Python script which normalizes a list of weights (given as commandline arguments) into a list of probabilities:
Produces output like this:
Useful script, but I’m not sure it’s necessary for this question. These aren’t exclusive or compared to each other. Each probability is independent, “likelihood that this topic will fit into lesswrong expectations”.