def main(argv):
try:
workDirResponsive = argv[0]
workDirPrivilege = argv[1]
numTestInstances = argv[2]
numTrainInstances = argv[3]
estimation_factor = float(numTestInstances) / float(numTrainInstances)
cMatrix = cm()
cMatrix.setCostMatrix(float(argv[4]), float(argv[5]), float(argv[6]),
float(argv[7]), float(argv[8]), float(argv[9]))
cMatrix.setAlpha(float(argv[10]))
cmv = cMatrix.getCostMatrix()
ccm = computeCm()
ccm.get_mcDocumentMatrix(
workDirResponsive + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTrainInstances) + '.p',
workDirResponsive + '/trainf.count.lables.dat',
workDirPrivilege + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTrainInstances) + '.p',
workDirPrivilege + '/trainf.count.lables.dat', cmv)
dMatrix = ccm.get_finalDocMatrix(estimation_factor)
Misclassification_cost = ccm.compute(dMatrix, cmv)
print "The misclassification cost is: ", Misclassification_cost
except:
raise
def main(argv):
try:
p2 = phase2()
wd = argv[
0] # Joint Cost Model's Working Directory (Resp and Priv Category )
workDirResponsive = argv[1] # Responsive Category Working Directory '
workDirPrivilege = argv[2] # Privilege Category Working Directory '
numTestInstances = argv[3]
rJFile = argv[4]
cMatrix = cm()
cMatrix.setCostMatrix(float(argv[5]), float(argv[6]), float(argv[7]),
float(argv[8]), float(argv[9]), float(argv[10]))
cMatrix.setAlpha(float(argv[11]))
cmv = cMatrix.getCostMatrix()
lamR = cMatrix.getLam_r()
p2.computeExpectation(
wd, numTestInstances, cmv, lamR,
workDirResponsive + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p',
workDirPrivilege + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p')
tau_rValue = p2.runphase2(
workDirResponsive + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p',
workDirPrivilege + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p', rJFile, wd, numTestInstances, 0)
except:
raise
def main(argv):
try:
p1 = phase1()
wDir = argv[
0] # Joint Cost Model's Working Directory (Specific Resp and Priv Cat , and) '/Users/jyothi/Documents/Research/jvdofs/rcv1v2/results' #arg[0]
workDirResponsive = argv[
1] # Responsive WD '/Users/jyothi/Documents/Research/jvdofs/rcv1v2/results/C15' #argv[1]
workDirPrivilege = argv[
2] # Privilege WD '/Users/jyothi/Documents/Research/jvdofs/rcv1v2/results/C17' # argv[2]
numTestInstances = argv[3] # 10000#argv[3]
cMatrix = cm()
cMatrix.setCostMatrix(float(argv[4]), float(argv[5]), float(argv[6]),
float(argv[7]), float(argv[8]), float(argv[9]))
cMatrix.setAlpha(float(argv[10]))
cmv = cMatrix.getCostMatrix()
p1.classifyDocuments(
wDir,
workDirResponsive + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p',
workDirPrivilege + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p',
numTestInstances,
cmv,
reclassify=False)
except:
raise
def main(argv):
try:
urbaseline = UncertainityRankingBaseline()
responsiveWD = argv[0]
privilegeWD = argv[1]
wd = argv[2]
rJf = argv[3]
pJf = argv[4]
numTestInstances = argv[5]
print "Starting Uncertainity Ranking Baseline Model "
cMatrix = cm()
cMatrix.setCostMatrix(float(argv[6]), float(argv[7]), float(argv[8]),
float(argv[9]), float(argv[10]), float(argv[11]))
cMatrix.setAlpha(float(argv[12]))
cmv = cMatrix.getCostMatrix()
urbaseline.run(
responsiveWD + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p',
privilegeWD + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p', wd,
wd + '/tauR_value.' + str(numTestInstances) + '.p',
wd + '/tauP_value.' + str(numTestInstances) + '.p', rJf, pJf,
numTestInstances, cmv)
except:
raise
def main(argv):
try:
wd=argv[0]
rJf=argv[1]
pJf=argv[2]
testSetSize=argv[3]
cMatrix=cm()
cMatrix.setCostMatrix(float(argv[4]),float(argv[5]),float(argv[6]),float(argv[7]),float(argv[8]),float(argv[9]))
cMatrix.setAlpha(float(argv[10]))
cmv=cMatrix.getCostMatrix()
baselineCall=FAB()
baselineCall.setJudgments(pJf,rJf)
baselineCall.compute_cost(wd+'/docid-D_P-risk.dictionary.'+str(testSetSize)+'.p',wd+'/docid-D_L-risk.dictionary.'+str(testSetSize)+'.p',wd+'/docid-D_W-risk.dictionary.'+str(testSetSize)+'.p',cmv)
except:
raise
def main(argv):
try:
wd=argv[0]#'/Users/jyothi/Documents/Research/jvdofs/results/temp/C15C17/'
rJf=argv[1]#'/Users/jyothi/Documents/Research/jvdofs/rcv1v2/datFiles/rcv1_C15.txt'
pJf=argv[2]#'/Users/jyothi/Documents/Research/jvdofs/rcv1v2/datFiles/rcv1_C17.txt'
testSetSize=argv[3]
cMatrix=cm()
cMatrix.setCostMatrix(float(argv[4]),float(argv[5]),float(argv[6]),float(argv[7]),float(argv[8]),float(argv[9]))
cMatrix.setAlpha(float(argv[10]))
cmv=cMatrix.getCostMatrix()
baselineCall=FAB()
baselineCall.setJudgments(pJf,rJf)
baselineCall.compute_cost(wd+'/docid-D_P-risk.dictionary.'+str(testSetSize)+'.p',wd+'/docid-D_L-risk.dictionary.'+str(testSetSize)+'.p',wd+'/docid-D_W-risk.dictionary.'+str(testSetSize)+'.p',cmv)
except:
raise
def main(argv):
try:
wd= argv[0] # Joint Cost Model's Working Directory (Specific Resp and Priv Cat )
numTestInstances=argv[1] # 10000#argv[3]
cMatrix=cm()
cMatrix.setCostMatrix(float(argv[2]),float(argv[3]),float(argv[4]),float(argv[5]),float(argv[6]),float(argv[7]))
cMatrix.setAlpha(float(argv[8]))
lamR=cMatrix.getLam_r()
lamP=cMatrix.getLam_p()
cca=computeCa()
cca.set_tauP(wd+'/tauP_value.'+str(numTestInstances)+'.p')
cca.set_tauR(wd+'/tauR_value.'+str(numTestInstances)+'.p')
annotation_cost = cca.compute(lamR,cca.get_tauR(),lamP,cca.get_tauP())
print "The total annotation cost is: ", annotation_cost
print "RESULTVALUE ",annotation_cost
except:
raise
def p1caller(pl, pw, lp, lw, wp, wl, alpha):
try:
costMatrix = cm()
costMatrix.setCostMatrix(float(pl), float(pw), float(lp), float(lw),
float(wp), float(wl))
costMatrix.setAlpha(float(alpha.strip()))
cmvalue = costMatrix.getCostMatrix()
p1 = phase1()
twd = '/app/data'
p1.classifyDocuments(
twd,
twd + '/GPOL-ds-op-label.tuple.dictionary.20000.p',
twd + '/ECAT-ds-op-label.tuple.dictionary.20000.p',
20000,
cmvalue,
reclassify=False)
except:
raise
def p3caller(pl, pw, lp, lw, wp, wl, alpha, lambda_P):
try:
costMatrix = cm()
costMatrix.setCostMatrix(float(pl), float(pw), float(lp), float(lw),
float(wp), float(wl))
costMatrix.setAlpha(float(alpha.strip()))
cmvalue = costMatrix.getCostMatrix()
lamP = float(lambda_P)
twd = '/app/data'
p3 = phase3()
p3.computeExpectation(
twd, 20000, cmvalue, lamP,
twd + '/ECAT-ds-op-label.tuple.dictionary.20000.p')
Tau_pValue = p3.runphase3(
twd + '/ECAT-ds-op-label.tuple.dictionary.20000.p',
twd + '/rcv1_ECAT.txt', twd, 20000, 0)
return Tau_pValue
except:
raise
def p2caller(pl, pw, lp, lw, wp, wl, alpha, lambda_R):
try:
costMatrix = cm()
costMatrix.setCostMatrix(float(pl), float(pw), float(lp), float(lw),
float(wp), float(wl))
costMatrix.setAlpha(float(alpha.strip()))
cmvalue = costMatrix.getCostMatrix()
lamR = lambda_R
p2 = phase2()
twd = '/app/data'
p2.computeExpectation(
twd, 20000, cmvalue, lamR,
twd + '/GPOL-ds-op-label.tuple.dictionary.20000.p',
twd + '/ECAT-ds-op-label.tuple.dictionary.20000.p')
Tau_rValue = p2.runphase2(
twd + '/GPOL-ds-op-label.tuple.dictionary.20000.p',
twd + '/ECAT-ds-op-label.tuple.dictionary.20000.p',
twd + '/rcv1_GPOL.txt', twd, 20000, 0)
return Tau_rValue
except:
raise
def main(argv):
try:
p1 = phase1()
wDir = argv[0]
workDirResponsive = argv[1]
workDirPrivilege = argv[2]
numTestInstances = argv[3]
cMatrix = cm()
cMatrix.setCostMatrix(float(argv[4]), float(argv[5]), float(argv[6]),
float(argv[7]), float(argv[8]), float(argv[9]))
cMatrix.setAlpha(float(argv[10]))
cmv = cMatrix.getCostMatrix()
p1.classifyDocuments(
wDir,
workDirResponsive + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p',
workDirPrivilege + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p',
numTestInstances,
cmv,
reclassify=False)
except:
raise
def main(argv):
try:
p3 = phase3()
wd = argv[
0] # Joint Cost Model's Working Directory (Specific Resp and Priv Cat )
workDirResponsive = argv[1] # Responsive WD '
workDirPrivilege = argv[2] # Privilege WD '
numTestInstances = argv[3]
pJFile = argv[4]
cMatrix = cm()
cMatrix.setCostMatrix(float(argv[5]), float(argv[6]), float(argv[7]),
float(argv[8]), float(argv[9]), float(argv[10]))
cMatrix.setAlpha(float(argv[11]))
cmv = cMatrix.getCostMatrix()
lamP = cMatrix.getLam_p()
p3.computeExpectation(
wd, numTestInstances, cmv, lamP,
workDirPrivilege + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p')
p3.runphase3(
workDirPrivilege + '/pickleFiles/ds-op-label.tuple.dictionary.' +
str(numTestInstances) + '.p', pJFile, wd, numTestInstances, 0)
except:
raise
def ComputeManualAnnotationCost(self,TAUr,TAUp):
cmobj=cm()
lam_r=cmobj.getLam_r()
lam_p=cmobj.getLam_p()
return (lam_r * TAUr + lam_p * TAUp)
