model5 = NodeAmountFeature(force_reload=reload, per_depth=True)
node_features = ClusterFeature(
CombineOperatorND(model0,
CombineOperatorND(model1,
CombineOperatorND(model2,
CombineOperatorND(model3,
CombineOperatorND(model4, model5))))),
combine=False,
force_reload=reload
)
model6 = ChainOperator(node_features, CommonStatistics(hstack=True))
features = ChainOperator(model6, Normalization(0,1))
export({
'features': features.compute(data.groups, data.labels),
'labels': features.get_labels(data),
'featureNames': features.get_feature_names(),
})
d = 0
for i, g in enumerate(data.groups):
c = 0
for n in g.nodes:
if n['sitename'] == 'wordreference_com' and c in node_features.index[i]:
print d+node_features.index[i].index(c), n['nodeName'], n['nodeText'], n['pos']
c += 1
d += len(node_features.index[i])
#_*_ coding: utf-8 _*_
from extractor import (
set_version,
export,
ResizeProcessing,
FrameworkFeature,
Normalization,
ChainOperator,
)
from dataset import DataSet
set_version('exp7')
data = DataSet('/home/gsj987/experiment/webscorer.new/groups/')
model0 = ResizeProcessing(0.3, 0.3, force_reload=True)
model1 = ChainOperator(model0, FrameworkFeature(pad=1, threshold=0.00015, min_width=4,force_reload=True))
o_features = model1
features = ChainOperator(o_features, Normalization(0,1))
export({
'features': features.compute(data.data, data.labels),
'labels': data.labels,
'featureNames': features.get_feature_names(),
})