def __test__():
import measure, datetime
data = [
{'a': 2, 'b': datetime.date(2003, 12, 5), 'c': 'A', 'cls': 1},
{'a': 7, 'b': datetime.date(2004, 12, 5), 'c': 'A', 'cls': 1},
{'a': 1, 'b': datetime.date(2007, 12, 5), 'c': 'A', 'cls': 2},
{'a': 9, 'b': datetime.date(2008, 12, 5), 'c': 'D', 'cls': 3},
{'a': 3, 'b': datetime.date(2009, 12, 5), 'c': 'B', 'cls': 1},
{'a': 2, 'b': datetime.date(2010, 12, 5), 'c': 'C', 'cls': 3},
]
entropy_impurity = measure.entropy(data, 'cls')
giniidx_impurity = measure.giniidx(data, 'cls')
cls_err_impurity = measure.cls_err(data, 'cls')
print 'split'
print ratio(data, 'a', 'cls', measure.entropy, entropy_impurity)
print ratio(data, 'a', 'cls', measure.giniidx, giniidx_impurity)
print ratio(data, 'a', 'cls', measure.cls_err, cls_err_impurity)
print 'nosplit'
print ratio(data, 'a', 'cls', measure.entropy, entropy_impurity, False)
print ratio(data, 'a', 'cls', measure.giniidx, giniidx_impurity, False)
print ratio(data, 'a', 'cls', measure.cls_err, cls_err_impurity, False)
print
print 'split'
print interval(data, 'b', 'cls', measure.entropy, entropy_impurity)
print interval(data, 'b', 'cls', measure.giniidx, giniidx_impurity)
print interval(data, 'b', 'cls', measure.cls_err, cls_err_impurity)
print 'nosplit'
print interval(data, 'b', 'cls', measure.entropy, entropy_impurity, False)
print interval(data, 'b', 'cls', measure.giniidx, giniidx_impurity, False)
print interval(data, 'b', 'cls', measure.cls_err, cls_err_impurity, False)
print
print 'split'
print ordinal(data, 'c', 'cls', measure.entropy, entropy_impurity)
print ordinal(data, 'c', 'cls', measure.giniidx, giniidx_impurity)
print ordinal(data, 'c', 'cls', measure.cls_err, cls_err_impurity)
print 'nosplit'
print ordinal(data, 'c', 'cls', measure.entropy, entropy_impurity, False)
print ordinal(data, 'c', 'cls', measure.giniidx, giniidx_impurity, False)
print ordinal(data, 'c', 'cls', measure.cls_err, cls_err_impurity, False)
print
print 'split'
print nominal(data, 'c', 'cls', measure.entropy, entropy_impurity)
print nominal(data, 'c', 'cls', measure.giniidx, giniidx_impurity)
print nominal(data, 'c', 'cls', measure.cls_err, cls_err_impurity)
print 'nosplit'
print nominal(data, 'c', 'cls', measure.entropy, entropy_impurity, False)
print nominal(data, 'c', 'cls', measure.giniidx, giniidx_impurity, False)
print nominal(data, 'c', 'cls', measure.cls_err, cls_err_impurity, False)
print
# print all combination of k and sd
for k in xrange(2, 5):
for sd_away in xrange(0, 5):
try:
kdist = dbscan.k_distance(dataset, k, sd_away)
except:
print 'kdist anchor out of range, skipped'
print
continue
cluster = dbscan.dbscan(dataset, kdist, k)
if len(cluster) == 0:
print 'k:', k, 'sd:', sd_away, 'kdist:', kdist, 'no. of cluster:', len(cluster)
print
continue
cc = [measure.cls_err(c) for c in cluster]
errs = []
clss = []
for err, cls in cc:
errs.append(err)
clss.append(cls)
cp = [len(c) for c in cluster]
print 'k:', k, 'sd:', sd_away, 'kdist:', kdist, 'no. of cluster:', len(cluster)
for i in xrange(0, len(cluster)):
print 'cluster:', i, 'no. of pt. in cluster:', cp[i], 'impurity (classification error):', errs[i], 'majority:', clss[i]
print 'mean impurity:', float(sum(errs)) / len(errs), 'sum of pt.:', sum(cp)
print
for sd_away in xrange(0, 5):
try:
kdist = dbscan.k_distance(dataset, k, sd_away)
except:
print 'kdist anchor out of range, skipped'
print
continue
cluster = dbscan.dbscan(dataset, kdist, k)
if len(cluster) == 0:
print 'k:', k, 'sd:', sd_away, 'kdist:', kdist, 'no. of cluster:', len(
cluster)
print
continue
cc = [measure.cls_err(c) for c in cluster]
errs = []
clss = []
for err, cls in cc:
errs.append(err)
clss.append(cls)
cp = [len(c) for c in cluster]
print 'k:', k, 'sd:', sd_away, 'kdist:', kdist, 'no. of cluster:', len(
cluster)
for i in xrange(0, len(cluster)):
print 'cluster:', i, 'no. of pt. in cluster:', cp[
i], 'impurity (classification error):', errs[
i], 'majority:', clss[i]
print 'mean impurity:', float(
sum(errs)) / len(errs), 'sum of pt.:', sum(cp)
def __test__():
import measure, datetime
data = [
{
'a': 2,
'b': datetime.date(2003, 12, 5),
'c': 'A',
'cls': 1
},
{
'a': 7,
'b': datetime.date(2004, 12, 5),
'c': 'A',
'cls': 1
},
{
'a': 1,
'b': datetime.date(2007, 12, 5),
'c': 'A',
'cls': 2
},
{
'a': 9,
'b': datetime.date(2008, 12, 5),
'c': 'D',
'cls': 3
},
{
'a': 3,
'b': datetime.date(2009, 12, 5),
'c': 'B',
'cls': 1
},
{
'a': 2,
'b': datetime.date(2010, 12, 5),
'c': 'C',
'cls': 3
},
]
entropy_impurity = measure.entropy(data, 'cls')
giniidx_impurity = measure.giniidx(data, 'cls')
cls_err_impurity = measure.cls_err(data, 'cls')
print 'split'
print ratio(data, 'a', 'cls', measure.entropy, entropy_impurity)
print ratio(data, 'a', 'cls', measure.giniidx, giniidx_impurity)
print ratio(data, 'a', 'cls', measure.cls_err, cls_err_impurity)
print 'nosplit'
print ratio(data, 'a', 'cls', measure.entropy, entropy_impurity, False)
print ratio(data, 'a', 'cls', measure.giniidx, giniidx_impurity, False)
print ratio(data, 'a', 'cls', measure.cls_err, cls_err_impurity, False)
print
print 'split'
print interval(data, 'b', 'cls', measure.entropy, entropy_impurity)
print interval(data, 'b', 'cls', measure.giniidx, giniidx_impurity)
print interval(data, 'b', 'cls', measure.cls_err, cls_err_impurity)
print 'nosplit'
print interval(data, 'b', 'cls', measure.entropy, entropy_impurity, False)
print interval(data, 'b', 'cls', measure.giniidx, giniidx_impurity, False)
print interval(data, 'b', 'cls', measure.cls_err, cls_err_impurity, False)
print
print 'split'
print ordinal(data, 'c', 'cls', measure.entropy, entropy_impurity)
print ordinal(data, 'c', 'cls', measure.giniidx, giniidx_impurity)
print ordinal(data, 'c', 'cls', measure.cls_err, cls_err_impurity)
print 'nosplit'
print ordinal(data, 'c', 'cls', measure.entropy, entropy_impurity, False)
print ordinal(data, 'c', 'cls', measure.giniidx, giniidx_impurity, False)
print ordinal(data, 'c', 'cls', measure.cls_err, cls_err_impurity, False)
print
print 'split'
print nominal(data, 'c', 'cls', measure.entropy, entropy_impurity)
print nominal(data, 'c', 'cls', measure.giniidx, giniidx_impurity)
print nominal(data, 'c', 'cls', measure.cls_err, cls_err_impurity)
print 'nosplit'
print nominal(data, 'c', 'cls', measure.entropy, entropy_impurity, False)
print nominal(data, 'c', 'cls', measure.giniidx, giniidx_impurity, False)
print nominal(data, 'c', 'cls', measure.cls_err, cls_err_impurity, False)
print