UnivariateTimeTypeToContinuous

UnivariateTimeTypeToContinuous

A model type for constructing a single variable transformer that creates continuous representations of temporally typed data, based on MLJModels.jl, and implementing the MLJ model interface.

From MLJ, the type can be imported using

UnivariateTimeTypeToContinuous = @load UnivariateTimeTypeToContinuous pkg=MLJModels

Do model = UnivariateTimeTypeToContinuous() to construct an instance with default hyper-parameters. Provide keyword arguments to override hyper-parameter defaults, as in UnivariateTimeTypeToContinuous(zero_time=...).

Use this model to convert vectors with a TimeType element type to vectors of Float64 type (Continuous element scitype).

Training data

In MLJ or MLJBase, bind an instance model to data with

mach = machine(model, x)

where

• x: any abstract vector whose element type is a subtype of Dates.TimeType

Train the machine using fit!(mach, rows=...).

Hyper-parameters

• zero_time: the time that is to correspond to 0.0 under transformations, with the type coinciding with the training data element type. If unspecified, the earliest time encountered in training is used.
• step::Period=Hour(24): time interval to correspond to one unit under transformation

Operations

• transform(mach, xnew): apply the encoding inferred when mach was fit

Fitted parameters

fitted_params(mach).fitresult is the tuple (zero_time, step) actually used in transformations, which may differ from the user-specified hyper-parameters.

Example

using MLJ
using Dates

x = [Date(2001, 1, 1) + Day(i) for i in 0:4]

encoder = UnivariateTimeTypeToContinuous(zero_time=Date(2000, 1, 1),
                                         step=Week(1))

mach = machine(encoder, x)
fit!(mach)
julia> transform(mach, x)
5-element Vector{Float64}:
 52.285714285714285
 52.42857142857143
 52.57142857142857
 52.714285714285715
 52.857142