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parallel ensembles #615

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parallel ensembles #615

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zmjones
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@zmjones zmjones commented Dec 15, 2015

this is not ready for merge but is here for review. the relevant issue is #603.

left to do are:

CostSensRegrWrapper
MultilabelBinaryRelevanceWrapper
CostSensWeightedPairsWrapper
StackedLearner

any others? I am currently parallelizing training and prediction using the same level.

i have written but haven't pushed tests for all of this.

@zmjones zmjones added this to the v2.8 milestone Dec 15, 2015
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zmjones commented Dec 21, 2015

what is the purpose of setting predict.type = "" the compression method for stacked learners?

@larskotthoff larskotthoff modified the milestones: v2.9, v2.8 Jan 12, 2016
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zmjones commented Jan 14, 2016

this is ready for review @berndbischl @larskotthoff. i think there are some wrappers i've missed but most are done now. training and prediction are parallelized, new tests added, etc.

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You've got some commented code in there that probably shouldn't be pulled in.

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zmjones commented Jan 14, 2016

fixed

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Thanks. Looks good to me!

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Are here still any problems, or why is this not merged? I mention parallelization in our multilabel paper (@bernd)...

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zmjones commented Jul 6, 2016

it was fine then but i'll have to rebase it

@giuseppec giuseppec mentioned this pull request Jul 6, 2016
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we will draw in the multilabel PR #977 first, then review here whether the multilabel ensembles work as well in parallel

@giuseppec giuseppec removed this from the v2.11 milestone Aug 8, 2016
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what is the purpose of setting predict.type = "" the compression method for stacked learners?

this will be removed, disregard pls

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pls note that PR #977 is pulled in now.
@zmjones please fix the conflicts and rebase this

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should be team reviewed with bb, @mllg and @zmjones

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zmjones commented Aug 8, 2016

ok will rebase asap.

@zmjones zmjones self-assigned this Aug 8, 2016
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fixes and level addition for partial predictions
3deebb6
@zmjones
ensemble wrapper parallelization
f460a68 
 - baggingwrapper
 - constsensregrwrapper
 - homogeneousensemble
 - multiclasswrapper
 - multilabelbinaryrelevancewrapper
 - overbaggingwrapper
 - stackedlearner
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zmjones commented Aug 10, 2016 •
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this is rebased now. the multilabel tests are the only thing that are failing now. in particular the only multilabel problem is the MultilabelDBRWrapper

@zmjones zmjones mentioned this pull request Aug 11, 2016
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@zmjones zmjones closed this Aug 11, 2016
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@zmjones @larskotthoff @PhilippPro @berndbischl @giuseppec @ja-thomas