def ruleText(self, rule):
text = orngCN2.ruleToString(rule, showDistribution=False)
p = re.compile(r"[0-9]\.[0-9]+")
text = p.sub(lambda match: "%.2f" % float(match.group()[0]), text)
text = text.replace("AND", "AND\n ")
text = text.replace("THEN", "\nTHEN")
return text
def saveRules(self):
fileName = str(
QFileDialog.getSaveFileName(self, "Rules", "Rules.txt", ".txt"))
try:
f = open(fileName, "w")
except:
return
for r in self.rules:
f.write(orngCN2.ruleToString(r) + "\n")
def selectAttributes(self):
import sets
selected = []
for r in self.selRect:
string = orngCN2.ruleToString(
r.rule)[2:].strip(" ").split("THEN")[0]
list = string.split("AND")
for l in list:
s = re.split("[=<>]", l.strip(" "))
selected.append(s[0])
selected = reduce(lambda l, r: (r in l) and l or l + [r], selected, [])
return selected
def ruleText(self, r):
str = orngCN2.ruleToString(r)
list = re.split("([0-9.]*)", str)
for i in range(len(list)):
try:
f = float(list[i])
list[i] = "%.3f" % f
t = int(list[i])
list[i] = str(t)
except:
pass
str = "".join(list)
list = re.split("<[0-9., ]*>$", str)
str = list[0]
str = "AND\n ".join(str.split("AND"))
str = "\nTHEN".join(str.split("THEN"))
return str
# Description: Demonstrates the use of orngABCN2 rules
# Category: classification, rules
# Classes: ABCN2, ABCN2Ordered, ABCN2M
# Uses: titanic.tab
import orange
import orngABCN2
import orngCN2
data = orange.ExampleTable("titanic.tab")
# create learner
learner = orngABCN2.ABCN2()
cl = learner(data)
for r in cl.rules:
print orngCN2.ruleToString(r)
print "*****"
learner = orngABCN2.ABCN2Ordered()
cl = learner(data)
for r in cl.rules:
print orngCN2.ruleToString(r)
print "*****"
learner = orngABCN2.ABCN2M()
cl = learner(data)
for r in cl.rules:
print orngCN2.ruleToString(r)
print "*****"
# Description: Demonstrates the use of orngCN2 rules
# Category: classification, rules
# Classes: CN2Learner, CN2UnorderedLearner, CN2UnorderedLearner
# Uses: titanic.tab
import Orange
import orngCN2
data = Orange.data.Table("titanic.tab")
# create learner
learner = orngCN2.CN2Learner()
cl = learner(data)
for r in cl.rules:
print orngCN2.ruleToString(r)
print "*****"
learner = orngCN2.CN2UnorderedLearner()
learner.ruleFinder = Orange.core.RuleBeamFinder()
learner.ruleFinder.evaluator = orngCN2.mEstimate(m=50)
cl = learner(data)
for r in cl.rules:
print orngCN2.ruleToString(r)
print "****"
learner = orngCN2.CN2SDUnorderedLearner()
learner.ruleFinder.ruleStoppingValidator = Orange.core.RuleValidator_LRS(alpha=0.01,min_coverage=10,max_rule_complexity = 2)