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transformer.jl
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transformer.jl
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"""
fit_transformer(data::CounterfactualData, input_encoder::Nothing; kwargs...)
Fit a transformer to the data. This is a no-op if `input_encoder` is `Nothing`.
"""
function fit_transformer(data::CounterfactualData, input_encoder::Nothing; kwargs...)
return nothing
end
"""
fit_transformer(data::CounterfactualData, input_encoder::InputTransformer; kwargs...)
Fit a transformer to the data for an `InputTransformer` object. This is a no-op.
"""
function fit_transformer(
data::CounterfactualData, input_encoder::InputTransformer; kwargs...
)
return input_encoder
end
"""
fit_transformer(
data::CounterfactualData,
input_encoder::Type{StatsBase.AbstractDataTransform};
kwargs...,
)
Fit a transformer to the data for a `StatsBase.AbstractDataTransform` object.
"""
function fit_transformer(
data::CounterfactualData,
input_encoder::Type{<:StatsBase.AbstractDataTransform};
kwargs...,
)
X = data.X
dt = StatsBase.fit(
input_encoder, X[transformable_features(data), :]; dims=ndims(X), kwargs...
)
return dt
end
"""
fit_transformer(
data::CounterfactualData,
input_encoder::Type{MultivariateStats.AbstractDimensionalityReduction};
kwargs...,
)
Fit a transformer to the data for a `MultivariateStats.AbstractDimensionalityReduction` object.
"""
function fit_transformer(
data::CounterfactualData,
input_encoder::Type{<:MultivariateStats.AbstractDimensionalityReduction};
kwargs...,
)
X = data.X
dt = MultivariateStats.fit(input_encoder, X; kwargs...)
return dt
end
"""
fit_transformer(
data::CounterfactualData,
input_encoder::Type{GenerativeModels.AbstractGenerativeModel};
kwargs...,
)
Fit a transformer to the data for a `GenerativeModels.AbstractGenerativeModel` object.
"""
function fit_transformer(
data::CounterfactualData,
input_encoder::Type{<:GenerativeModels.AbstractGenerativeModel};
kwargs...,
)
X = data.X
dt = GenerativeModels._fit(input_encoder, X; kwargs...)
return dt
end