def run_validation(dominios, folds, featureVector, participantesInput, incluirParticipante):
[inputs, frequencias, participantes] = [{}, {}, {}]
# Inicializa Vetor de Caracteristicas
for fold in folds:
frequencias[fold] = utils.countAttributeFrequencyIndividual(folds, fold)
participantes[fold] = parser.descriptionsMeans(folds, fold, participantesInput, dominios)
inputs[fold] = parser.parseSVMInput(
folds[fold], featureVector, participantes[fold], frequencias[fold], incluirParticipante
)
[acertos, total] = [{}, {}]
keys = folds.keys()
keys.sort()
for fold in folds:
# print "Fold: ", fold
# print 50 * "-"
resultados = svm.run(inputs, fold)
for combination in resultados.keys():
if combination not in acertos.keys():
acertos[combination] = {}
total[combination] = {}
for svm1 in resultados[combination][0].keys():
if svm1 not in acertos[combination].keys():
acertos[combination][svm1] = 0.0
total[combination][svm1] = 0.0
acertos[combination][svm1] = acertos[combination][svm1] + resultados[combination][0][svm1]
total[combination][svm1] = total[combination][svm1] + resultados[combination][1][svm1]
combinacoes = {}
acuracias = {}
for combination in acertos.keys():
aux = combination.split(",")
C = float(aux[0])
gamma = float(aux[1])
# print 20 * "-"
# print str(C) + " - " + str(gamma)
# print 20 * "-"
for svm1 in acertos[combination].keys():
if total[combination][svm1] == 0:
acuracia = 0
else:
acuracia = acertos[combination][svm1] / total[combination][svm1]
# print str(svm1) + ": " + str(acuracia)
if svm1 not in combinacoes.keys():
acuracias[svm1] = acuracia
combinacoes[svm1] = {}
combinacoes[svm1]["C"] = C
combinacoes[svm1]["gamma"] = gamma
elif acuracia > acuracias[svm1]:
acuracias[svm1] = acuracia
combinacoes[svm1]["C"] = C
combinacoes[svm1]["gamma"] = gamma
return combinacoes
def run(dominios, targets, folds, atributos, participantesInput, incluirParticipante):
featureVector = parser.parseFeatureVector(dominios, targets)
inputs = {}
frequencias = {}
participantes = {}
# Inicializa Vetor de Caracteristicas
for fold in folds:
frequencias[fold] = utils.countAttributeFrequencyIndividual(folds, fold)
participantes[fold] = parser.descriptionsMeans(folds, fold, dominios)
inputs[fold] = parser.parseSVMInput(folds[fold], featureVector, participantes[fold], frequencias[fold], incluirParticipante)
resultadoTotal = []
diceTotal = []
masiTotal = []
acuraciaTotal = 0.0
for testeFold in folds:
teste = folds[testeFold]
inputTeste = inputs[testeFold]
treinamentoFolds = {}
inputsTreinamento = {}
for foldAux in folds:
if foldAux != testeFold:
treinamentoFolds[foldAux] = folds[foldAux]
inputsTreinamento[foldAux] = inputs[foldAux]
combinacoes = run_validation(dominios, treinamentoFolds, featureVector, participantesInput, incluirParticipante)
resultados = svm.run2(inputsTreinamento, inputTeste, combinacoes)
resultadoTotal.append(resultados)
acertos = resultados[0]
total = resultados[1]
expressoes = resultados[2]
tp = resultados[3]
tn = resultados[4]
fp = resultados[5]
fn = resultados[6]
dice = []
masi = []
acuracia = 0
for expressao in expressoes:
contexto = expressao["anotacao"]["caracteristicas"]["context"]
descricao = utils.defineExpressao(expressao["previsoes"], dominios[contexto], targets[contexto])
descricaoR = expressao["anotacao"]["descricao"]
A = ass.parse(descricao)
B = ass.parse(descricaoR)
DICE = ass.dice(A, B)
MASI = ass.masi(A, B)
# print 20 * "-"
# print descricaoR
# print descricao
# print DICE
# print 20 * "-"
if DICE == 1.0:
acuracia = acuracia + 1.0
acuraciaTotal = acuraciaTotal + 1.0
dice.append(DICE)
masi.append(MASI)
diceTotal.append(DICE)
masiTotal.append(MASI)
# for atributo in acertos.keys():
# print "Attribute: " + str(atributo)
# print "Accuracy: " + str(acertos[atributo] / total[atributo])
# print 10 * "-"
#
# print 50 * "*"
#
# print "\n"
# print "General:"
# print 50 * "*"
# print "Expressions: "
# print "Dice: " + str(np.mean(dice))
# print "Masi: " + str(np.mean(masi))
# print "Accuracy: " + str(acuracia / len(dice))
# print "\n"
# print "\n"
# print "General:"
# print 50 * "*"
# print "Expressions: "
# print "Dice: " + str(np.mean(diceTotal))
# print "Masi: " + str(np.mean(masiTotal))
# print "Accuracy: " + str(acuraciaTotal / len(diceTotal))
# print "\n"
acertosT = {}
totalT = {}
for resultados in resultadoTotal:
acertos = resultados[0]
total = resultados[1]
for atributo in acertos.keys():
if atributo not in acertosT:
acertosT[atributo] = 0.0
totalT[atributo] = 0.0
acertosT[atributo] = acertosT[atributo] + acertos[atributo]
totalT[atributo] = totalT[atributo] + total[atributo]
# print "Attributes:"
# print 15 * "-"
# for atributo in acertosT.keys():
# print "Attribute: " + str(atributo)
# print "Accuracy: " + str(acertosT[atributo] / totalT[atributo])
# print 10 * "-"
return resultadoTotal, diceTotal, masiTotal, acuraciaTotal
