def svm_loss(model_table, dat_table, label, arr, epoch):
''' Compute the SVM loss
'''
return iutil.bismarck_query(
'sum(svmloss(__PREV_MODEL__, %(arr)s, %(label)s))' % {
'arr': arr,
'label': label
}, model_table, dat_table, epoch, label)
def logr_loss(model_table, dat_table, label, arr, epoch):
''' Computes the loss for each example in the data table
@param model_table: name of table to store models
@param dat_table: name of table we iterate over
@param label: name of label column
@param arr: UDF that returns an double array stored as a string
@param epoch: the epoch number (which model # to use when computing the loss)
'''
return iutil.bismarck_query('logrloss(__PREV_MODEL__, %(arr)s, %(label)s)' %
{'arr':arr, 'label':label}, model_table, dat_table, epoch, label)
def logr_loss(model_table, dat_table, label, arr, epoch):
''' Computes the loss for each example in the data table
@param model_table: name of table to store models
@param dat_table: name of table we iterate over
@param label: name of label column
@param arr: UDF that returns an double array stored as a string
@param epoch: the epoch number (which model # to use when computing the loss)
'''
return iutil.bismarck_query('logrloss(__PREV_MODEL__, %(arr)s, %(label)s)' %
{'arr':arr, 'label':label}, model_table, dat_table, epoch, label)
def svm_loss(model_table, dat_table, label, arr, epoch):
''' Compute the SVM loss
'''
return iutil.bismarck_query('sum(svmloss(__PREV_MODEL__, %(arr)s, %(label)s))' %
{'arr':arr, 'label':label}, model_table, dat_table, epoch, label)
