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Relax restrictions on model type in resampling (evaluate!) #985

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Jul 7, 2024
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Relax restrictions on model type in resampling (evaluate!) #985

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2209563
relax restrictions on model type in resampling
ablaom Jun 30, 2024
140fb7b
add catch for missing target in resampling
ablaom Jul 1, 2024
64b9481
code comment typo
ablaom Jul 1, 2024
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46 changes: 35 additions & 11 deletions src/resampling.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -31,10 +31,6 @@ const ERR_INVALID_OPERATION = ArgumentError(
_ambiguous_operation(model, measure) =
"`$measure` does not support a `model` with "*
"`prediction_type(model) == :$(prediction_type(model))`. "
err_ambiguous_operation(model, measure) = ArgumentError(
_ambiguous_operation(model, measure)*
"\nUnable to infer an appropriate operation for `$measure`. "*
"Explicitly specify `operation=...` or `operations=...`. ")
err_incompatible_prediction_types(model, measure) = ArgumentError(
_ambiguous_operation(model, measure)*
"If your model is truly making probabilistic predictions, try explicitly "*
Expand Down Expand Up @@ -65,11 +61,37 @@ ERR_MEASURES_DETERMINISTIC(measure) = ArgumentError(
"and so is not supported by `$measure`. "*LOG_AVOID
)

# ==================================================================
## MODEL TYPES THAT CAN BE EVALUATED
err_ambiguous_operation(model, measure) = ArgumentError(
_ambiguous_operation(model, measure)*
"\nUnable to infer an appropriate operation for `$measure`. "*
"Explicitly specify `operation=...` or `operations=...`. "*
"Possible value(s) are: $PREDICT_OPERATIONS_STRING. "
)

const ERR_UNSUPPORTED_PREDICTION_TYPE = ArgumentError(
"""

# not exported:
const Measurable = Union{Supervised, Annotator}
The `prediction_type` of your model needs to be one of: `:deterministic`,
`:probabilistic`, or `:interval`. Does your model implement one of these operations:
$PREDICT_OPERATIONS_STRING? If so, you can try explicitly specifying `operation=...`
or `operations=...` (and consider posting an issue to have the model review it's
definition of `MLJModelInterface.prediction_type`). Otherwise, performance
evaluation is not supported.

"""
)

const ERR_NEED_TARGET = ArgumentError(
"""

To evaluate a model's performance you must provide a target variable `y`, as in
`evaluate(model, X, y; options...)` or

mach = machine(model, X, y)
evaluate!(mach; options...)

"""
)

# ==================================================================
## RESAMPLING STRATEGIES
Expand Down Expand Up @@ -987,7 +1009,7 @@ function _actual_operations(operation::Nothing,
throw(err_ambiguous_operation(model, m))
end
else
throw(err_ambiguous_operation(model, m))
throw(ERR_UNSUPPORTED_PREDICTION_TYPE)
end
end
end
Expand Down Expand Up @@ -1137,7 +1159,7 @@ See also [`evaluate`](@ref), [`PerformanceEvaluation`](@ref),

"""
function evaluate!(
mach::Machine{<:Measurable};
mach::Machine;
resampling=CV(),
measures=nothing,
measure=measures,
Expand All @@ -1160,6 +1182,8 @@ function evaluate!(
# weights, measures, operations, and dispatches a
# strategy-specific `evaluate!`

length(mach.args) > 1 || throw(ERR_NEED_TARGET)

repeats > 0 || error("Need `repeats > 0`. ")

if resampling isa TrainTestPairs
Expand Down Expand Up @@ -1235,7 +1259,7 @@ Returns a [`PerformanceEvaluation`](@ref) object.
See also [`evaluate!`](@ref).

"""
evaluate(model::Measurable, args...; cache=true, kwargs...) =
evaluate(model::Model, args...; cache=true, kwargs...) =
evaluate!(machine(model, args...; cache=cache); kwargs...)

# -------------------------------------------------------------------
Expand Down
32 changes: 31 additions & 1 deletion test/resampling.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,8 @@ end
struct DummyInterval <: Interval end
dummy_interval=DummyInterval()

struct GoofyTransformer <: Unsupervised end

dummy_measure_det(yhat, y) = 42
API.@trait(
typeof(dummy_measure_det),
Expand Down Expand Up @@ -115,6 +117,12 @@ API.@trait(
MLJBase.err_ambiguous_operation(dummy_interval, LogLoss()),
MLJBase._actual_operations(nothing,
[LogLoss(), ], dummy_interval, 1))

# model does not have a valid `prediction_type`:
@test_throws(
MLJBase.ERR_UNSUPPORTED_PREDICTION_TYPE,
MLJBase._actual_operations(nothing, [LogLoss(),], GoofyTransformer(), 0),
)
end

@everywhere begin
Expand Down Expand Up @@ -935,7 +943,29 @@ end
end
end

# DUMMY LOGGER

# # TRANSFORMER WITH PREDICT

struct PredictingTransformer <:Unsupervised end
MLJBase.fit(::PredictingTransformer, verbosity, X, y) = (mean(y), nothing, nothing)
MLJBase.fit(::PredictingTransformer, verbosity, X) = (nothing, nothing, nothing)
MLJBase.predict(::PredictingTransformer, fitresult, X) = fill(fitresult, nrows(X))
MLJBase.predict(::PredictingTransformer, ::Nothing, X) = nothing
MLJBase.prediction_type(::Type{<:PredictingTransformer}) = :deterministic

@testset "`Unsupervised` model with a predict" begin
X = rand(10)
y = fill(42.0, 10)
e = evaluate(PredictingTransformer(), X, y, resampling=Holdout(), measure=l2)
@test e.measurement[1] ≈ 0
@test_throws(
MLJBase.ERR_NEED_TARGET,
evaluate(PredictingTransformer(), X, measure=l2),
)
end


# # DUMMY LOGGER

struct DummyLogger end

Expand Down
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