filter_correlated.py
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filter_correlated.py
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	"""
	Input: 2 bin names? or do it at higher level?

	Output:
	determine if two bins should be treated as correlated or not
	can be done statically from our DB
	"""

	def correlation_strategy():
	"""
	If correlated: keep only the better excluded bin
	"""
	pass

	"""
	Combine output of confidence_level : (s,b,n; CL)
	for independent bins
	into ([s...],[b...],[n...]) to prepare for recalculating CL
	"""


	"""
	Could get one global CL this way, or CLs at any desired level
	"""