def getTopProducts(doc_set, feature, dep_feature, num_products):
ai = AttrInfo.lookup(feature)
if ai is None:
raise Exception("unknown feature: {0}".format(feature))
mult = 1
if ai.name == "price":
mult = -1
if not ai.is_discrete:
buckets = bucketByPercentile(doc_set, feature, num_products)
return filter(lambda x: x is not None, [
argmax(b, lambda x: x.normalized[dep_feature], mult)
for b in buckets
])
else:
bucketed = [
filter(lambda x: x.normalized[feature] == v, doc_set)
for v in ai.values
]
prods = [
argmax(b, lambda x: x.normalized[dep_feature], mult)
for b in bucketed
]
prods = filter(lambda x: x is not None, prods)
return argmaxTake(prods, dep_feature, num_products, mult)
def getTopProducts(doc_set, feature, dep_feature, num_products):
ai = AttrInfo.lookup(feature)
if ai is None:
raise Exception("unknown feature: {0}".format(feature))
mult = 1
if ai.name == "price":
mult = -1
if not ai.is_discrete:
buckets = bucketByPercentile(doc_set, feature, num_products)
return filter(lambda x: x is not None,
[argmax(b, lambda x: x.normalized[dep_feature], mult) for b in buckets])
else:
bucketed = [filter(lambda x: x.normalized[feature] == v, doc_set) for v in ai.values]
prods = [argmax(b, lambda x: x.normalized[dep_feature], mult) for b in bucketed]
prods = filter(lambda x: x is not None, prods)
return argmaxTake(prods, dep_feature, num_products, mult)
