pjautoml.cs.operator.datadriven.optimization.modelfree.random.RandomSearch

class pjautoml.cs.operator.datadriven.optimization.modelfree.random.RandomSearch(cs, sample=100, best=1, train=<class 'pjdata.content.specialdata.NoData'>, test=<class 'pjdata.content.specialdata.NoData'>)[source]
__init__(cs, sample=100, best=1, train=<class 'pjdata.content.specialdata.NoData'>, test=<class 'pjdata.content.specialdata.NoData'>)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(cs[, sample, best, train, test]) Initialize self.
disable_pretty_printing() Disable the pretty-printing.
enable_pretty_printing() Enable the pretty-printing.
sample() The sample method will behave like a circular list.

Attributes

cs TODO.
jsonable
name Return the name of the CS.
path Return the name of the CS.
pretty_printing
cs[source]

TODO.

disable_pretty_printing()[source]

Disable the pretty-printing.

enable_pretty_printing()[source]

Enable the pretty-printing.

name[source]

Return the name of the CS.

path[source]

Return the name of the CS.

sample()[source]

The sample method will behave like a circular list. Therefore, it returns the first example to the last and the first again.