def rankFeatures(selectionType, dataFilePath, outputFilePath):
examples = orange.ExampleTable(dataFilePath)
attMeasures = eval(selectionType)
rankedFeatures = orngFSS.bestNAtts(attMeasures, len(examples.domain.attributes))
rankedFeatures = [examples.domain[feature].name for feature in rankedFeatures]
examples = None
outFile = open(outputFilePath, 'w')
for rankedFeature in rankedFeatures:
outFile.write(rankedFeature + "\n")
outFile.close()
def rankFeatures(selectionType, dataFilePath, outputFilePath):
examples = orange.ExampleTable(dataFilePath)
attMeasures = eval(selectionType)
rankedFeatures = orngFSS.bestNAtts(attMeasures, len(examples.domain.attributes))
rankedFeatures = [examples.domain[feature].name for feature in rankedFeatures]
examples = None
outFile = open(outputFilePath, 'w')
for rankedFeature in rankedFeatures:
outFile.write(rankedFeature + "\n")
outFile.close()
# Description: Ranking and selection of best N attributes
# Category: preprocessing
# Uses: voting
# Referenced: orngFSS.htm
# Classes: orngFSS.attMeasure, orngFSS.bestNAtts
import orange, orngFSS
data = orange.ExampleTable("voting")
print 'Attribute scores for best three attributes:'
ma = orngFSS.attMeasure(data)
for m in ma[:3]:
print "%5.3f %s" % (m[1], m[0])
n = 3
best = orngFSS.bestNAtts(ma, n)
print '\nBest %d attributes:' % n
for s in best:
print s
