KFold

PortfolioOptimisers.KFold Type

struct KFold{T1, T2, T3} <: NonSequentialCrossValidationEstimator
    n::T1
    purged_size::T2
    embargo_size::T3
end

Implements non-sequential k-fold cross-validation with optional purging and embargoing of training samples.

Fields

• n: Number of folds to split the data into.

• purged_size: Number of observations to exclude from the start/end of each train set adjacent to a test set.

• embargo_size: Number of observations to exclude from the start of each train set after a test set.

Constructors

KFold(; n::Integer = 5, purged_size::Integer = 0, embargo_size::Integer = 0)

Keyword arguments correspond to the fields above.

Validation

• n must be non-empty, greater than zero, and finite.

• purged_size and embargo_size must be non-empty and finite.

Examples

julia> KFold(; n = 5, purged_size = 7, embargo_size = 11)
KFold
             n ┼ Int64: 5
   purged_size ┼ Int64: 7
  embargo_size ┴ Int64: 11

Related

• [NonSequentialCrossValidationEstimator]-(@ref)

• [KFoldResult]-(@ref)

• [split]-(@ref)

• [n_splits]-(@ref)

source