def test1(self):
# " testing pruning with known results "
oPts = [
[0, 0, 1, 0],
[0, 1, 1, 1],
[1, 0, 1, 1],
[1, 1, 0, 0],
[1, 1, 1, 1],
]
tPts = oPts + [[0, 1, 1, 0], [0, 1, 1, 0]]
tree = ID3.ID3Boot(oPts, attrs=range(3), nPossibleVals=[2] * 4)
err, badEx = CrossValidate.CrossValidate(tree, oPts)
assert err == 0.0, 'bad initial error'
assert len(badEx) == 0, 'bad initial error'
# prune with original data, shouldn't do anything
f = StringIO()
with redirect_stdout(f):
PruneTree._verbose = True
newTree, err = PruneTree.PruneTree(tree, [], oPts)
PruneTree._verbose = False
self.assertIn('Pruner', f.getvalue())
assert newTree == tree, 'improper pruning'
# prune with train data
newTree, err = PruneTree.PruneTree(tree, [], tPts)
assert newTree != tree, 'bad pruning'
assert feq(err, 0.14286), 'bad error result'
def test1(self):
" testing pruning with known results "
oPts= [ \
[0,0,1,0],
[0,1,1,1],
[1,0,1,1],
[1,1,0,0],
[1,1,1,1],
]
tPts = oPts+[[0,1,1,0],[0,1,1,0]]
tree = ID3.ID3Boot(oPts,attrs=range(3),nPossibleVals=[2]*4)
err,badEx = CrossValidate.CrossValidate(tree,oPts)
assert err==0.0,'bad initial error'
assert len(badEx)==0,'bad initial error'
# prune with original data, shouldn't do anything
newTree,err = PruneTree.PruneTree(tree,[],oPts)
assert newTree==tree,'improper pruning'
# prune with train data
newTree,err = PruneTree.PruneTree(tree,[],tPts)
assert newTree!=tree,'bad pruning'
assert feq(err,0.14286),'bad error result'
def Grow(self,
examples,
attrs,
nPossibleVals,
nTries=10,
pruneIt=0,
lessGreedy=0):
""" Grows the forest by adding trees
**Arguments**
- examples: the examples to be used for training
- attrs: a list of the attributes to be used in training
- nPossibleVals: a list with the number of possible values each variable
(as well as the result) can take on
- nTries: the number of new trees to add
- pruneIt: a toggle for whether or not the tree should be pruned
- lessGreedy: toggles the use of a less greedy construction algorithm where
each possible tree root is used. The best tree from each step is actually
added to the forest.
"""
self._nPossible = nPossibleVals
for i in range(nTries):
tree, frac = CrossValidate.CrossValidationDriver(
examples,
attrs,
nPossibleVals,
silent=1,
calcTotalError=1,
lessGreedy=lessGreedy)
if pruneIt:
tree, frac2 = PruneTree.PruneTree(tree,
tree.GetTrainingExamples(),
tree.GetTestExamples(),
minimizeTestErrorOnly=0)
print('prune: ', frac, frac2)
frac = frac2
self.AddTree(tree, frac)
if i % (nTries / 10) == 0:
print('Cycle: % 4d' % (i))
def test_exampleCode(self):
f = StringIO()
with redirect_stdout(f):
try:
PruneTree._testRandom()
self.assertTrue(os.path.isfile('prune.pkl'))
finally:
if os.path.isfile('orig.pkl'):
os.remove('orig.pkl')
if os.path.isfile('prune.pkl'):
os.remove('prune.pkl')
self.assertIn('pruned error', f.getvalue())
f = StringIO()
with redirect_stdout(f):
PruneTree._testSpecific()
self.assertIn('pruned holdout error', f.getvalue())
f = StringIO()
with redirect_stdout(f):
PruneTree._testChain()
self.assertIn('pruned holdout error', f.getvalue())
def test_exampleCode(self):
f = StringIO()
with redirect_stdout(f):
try:
PruneTree._testRandom()
self.assertTrue(os.path.isfile('prune.pkl'))
finally:
if os.path.isfile('orig.pkl'):
os.remove('orig.pkl')
if os.path.isfile('prune.pkl'):
os.remove('prune.pkl')
self.assertIn('pruned error', f.getvalue())
f = StringIO()
with redirect_stdout(f):
PruneTree._testSpecific()
self.assertIn('pruned holdout error', f.getvalue())
f = StringIO()
with redirect_stdout(f):
PruneTree._testChain()
self.assertIn('pruned holdout error', f.getvalue())