Closed johannes-kk closed 4 years ago
Most of the DataFrame
functions use DataVector
objects, which seem to cause some occasional bad malloc
requests with OpenMP. There is also limited looping, hence the only basic data structure parallelisation that seemed reasonable was DataFrame.sample()
when using replacement. See #112 .
For Losses
the only real looping is done across response classes, which in the binary case means only two. As we focus on binary classification, parallelising Losses
is entirely redundant.
LossFunction
,DataFrame
, etc.