def recordAccModel(modelName, dataset):
strDeepModel, h, trainTime, prec, recall, strConfMat, predAtK = trainTest(
modelName, dataset)
currTime = datetime.datetime.now().ctime()
numPairs = dataset.getTotalNumPairs()
tvt = (round(CF.TRAIN_SPLIT, 2), round(CF.VALIDATION_SPLIT, 2),
round(1 - CF.TRAIN_SPLIT - CF.VALIDATION_SPLIT, 2))
dict_index, num_classes = dataset.dict_Cluster_Index, dataset.num_classes
if dataset.multiClass:
dict_index, num_classes = dataset.dict_Label_Index, dataset.num_labels
classMapStr = '\n'.join(
[str(j) + ' -> ' + str(i) for i, j in H.sortDictVal(dict_index)])
row = [currTime, trainSet, predictSet, numPairs, tvt, num_classes - 1]
row += [
modelName, strDeepModel, predAtK, prec, recall, trainTime,
dataset.max_seq_length, dataset.max_vocab_size
]
row += [TRAIN_MULT_FACTOR, EPOCHS, CF.EMBEDDING_VECTOR_LENGTH]
row += [
classMapStr, strConfMat,
roundH(h, 'acc'),
roundH(h, 'loss'),
roundH(h, 'val_acc'),
roundH(h, 'val_loss')
]
writeSummary(row)
def getCSV_Conf(self):
return [(k, v)
for k, v in H.sortDictVal(self.predClasses, reverse=True)]