KFold

class KFold(*args)

K-fold.

Parameters:

kpositive integer

Number of folds in which the sample is split. If not provided, default is .

See also

FittingAlgorithm, CorrectedLeaveOneOut

Notes

KFold inherits from FittingAlgorithm.

Examples

>>> import openturns as ot
>>> size = 100
>>> xuniform = ot.Uniform(0.9, 1.1)
>>> x = xuniform.getSample(size)
>>> yuniform = ot.Uniform(1.9, 2.1)
>>> y = yuniform.getSample(size)
>>> w = [1.0] * size
>>> f = ot.SymbolicFunction(['x'], ['2.0 * x'])
>>> basis = [f]
>>> indices = [0]
>>> fittingAlgo = ot.KFold()
>>> result = fittingAlgo.run(x, y, w, basis, indices)

Methods

getClassName()	Accessor to the object's name.
getId()	Accessor to the object's id.
getK()	Accessor to the number of folds.
getName()	Accessor to the object's name.
getShadowedId()	Accessor to the object's shadowed id.
getVisibility()	Accessor to the object's visibility state.
hasName()	Test if the object is named.
hasVisibleName()	Test if the object has a distinguishable name.
run(x, y, weight, basis, indices)	Run the algorithm.
setK(p)	Accessor to the number of folds.
setName(name)	Accessor to the object's name.
setShadowedId(id)	Accessor to the object's shadowed id.
setVisibility(visible)	Accessor to the object's visibility state.

__init__(*args)

getClassName()

Accessor to the object’s name.

Returns:

class_namestr

The object class name (object.__class__.__name__).

getId()

Accessor to the object’s id.

Returns:

idint

Internal unique identifier.

getK()

Accessor to the number of folds.

Returns:

kinteger

Number of folds in which the sample is split.

getName()

Accessor to the object’s name.

Returns:

namestr

The name of the object.

getShadowedId()

Accessor to the object’s shadowed id.

Returns:

idint

Internal unique identifier.

getVisibility()

Accessor to the object’s visibility state.

Returns:

visiblebool

Visibility flag.

hasName()

Test if the object is named.

Returns:

hasNamebool

True if the name is not empty.

hasVisibleName()

Test if the object has a distinguishable name.

Returns:

hasVisibleNamebool

True if the name is not empty and not the default one.

run(x, y, weight, basis, indices)

Run the algorithm.

Parameters:

x2-d sequence of float

Input sample

y2-d sequence of float

Output sample

weightsequence of float

Weights associated to the outputs

psisequence of Function

Basis

indicessequence of int

Indices of the basis

Returns:

measurefloat

Fitting measure

setK(p)

Accessor to the number of folds.

Parameters:

kinteger

Number of folds in which the sample is split.

setName(name)

Accessor to the object’s name.

Parameters:

namestr

The name of the object.

setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters:

idint

Internal unique identifier.

setVisibility(visible)

Accessor to the object’s visibility state.

Parameters:

visiblebool

Visibility flag.

Examples using the class

Trend computation

Trend computation