Plot Support vs Confidence for BigML promotional sources

support_vs_confidence.py

from bigml.api import BigML
from bigml.model import Model
api = BigML()

def support_vs_confidence(model_id):
	model = api.get_model(model_id)
	local_model = Model(model)
	leaves = local_model.get_leaves()
	outputs = unique([leaf['output'] for leaf in leaves])
	colors = linspace(0, 1, len(outputs))
	colordict = dict(zip(outputs, colors))
	total_count = float(reduce(lambda x,y: x+y, [leaf['count'] for leaf in leaves]))
	support =  [leaf['count']/total_count for leaf in leaves]
	confidence = [leaf['confidence'] for leaf in leaves]
	output = [colordict[leaf['output']] for leaf in leaves]
	scatter(support, confidence, c=output)
	title(model['object']['name'])
	xlabel("support")
	ylabel("confidence")

figure()
subplot(221)
support_vs_confidence('model/51553a43035d0731c3000143')

subplot(222)
support_vs_confidence('model/51553a48035d0731be00017c')

subplot(223)
support_vs_confidence('model/51553a4d0c0b5e04c4000150')

subplot(224)
support_vs_confidence('model/51553a520c0b5e04c5000278')

show()