I'm guessing that the example below failures because you assume the target is a categorical vector whose "raw" type is Bool. However, it could be any type (in this case it is String). The example does not error if I insert the following code immediately after the unpack line:
y = map(y) do η
η == "1" ? true : false
end
The example:
using MLJFair, MLJ
import DataFrames
model = @pipeline ContinuousEncoder @load(EvoTreeClassifier)
# load Indian Liver Patient Dataset:
data = OpenML.load(1480) |> DataFrames.DataFrame ;
y, X = unpack(data, ==(:Class), name->true; rng=123);
y = coerce(y, Multiclass);
coerce!(X, :V2 => Multiclass, Count => Continuous);
schema(X)
# Notes:
# - The target `y` is 1 for liver patients, 2 otherwise
# - The attribute `V2` of `X` is gender
wrappedModel = ReweighingSamplingWrapper(model, grp=:V2)
julia> evaluate(wrappedModel,
X, y,
measures=MetricWrappers(
[true_positive, true_positive_rate]; grp=:V2))
ERROR: MethodError: Cannot `convert` an object of type String to an object of type Bool
Closest candidates are:
convert(::Type{T}, ::T) where T<:Number at number.jl:6
convert(::Type{T}, ::Number) where T<:Number at number.jl:7
convert(::Type{T}, ::Ptr) where T<:Integer at pointer.jl:23
...
Stacktrace:
[1] convert(::Type{Bool}, ::CategoricalArrays.CategoricalValue{String,UInt32}) at /Users/anthony/.julia/packages/CategoricalArrays/nd8kj/src/value.jl:68
[2] setindex!(::Array{Bool,1}, ::CategoricalArrays.CategoricalValue{String,UInt32}, ::Int64) at ./array.jl:782
[3] copyto! at ./abstractarray.jl:807 [inlined]
[4] copyto! at ./abstractarray.jl:799 [inlined]
[5] AbstractArray at ./array.jl:499 [inlined]
[6] convert at ./abstractarray.jl:16 [inlined]
[7] fair_tensor(::CategoricalArrays.CategoricalArray{String,1,UInt32,String,CategoricalArrays.CategoricalValue{String,UInt32},Union{}}, ::CategoricalArrays.CategoricalArray{String,1,UInt32,String,CategoricalArrays.CategoricalValue{String,UInt32},Union{}}, ::CategoricalArrays.CategoricalArray{String,1,UInt32,String,CategoricalArrays.CategoricalValue{String,UInt32},Union{}}) at /Users/anthony/Dropbox/Julia7/MLJ/MLJFair/src/fair_tensor.jl:54
[8] (::MetricWrapper)(::MLJBase.UnivariateFiniteArray{Multiclass{2},String,UInt32,Float32,1}, ::DataFrames.DataFrame, ::CategoricalArrays.CategoricalArray{String,1,UInt32,String,CategoricalArrays.CategoricalValue{String,UInt32},Union{}}) at /Users/anthony/Dropbox/Julia7/MLJ/MLJFair/src/measures/metricWrapper.jl:50
[9] value at /Users/anthony/.julia/packages/MLJBase/r3heT/src/measures/measures.jl:74 [inlined]
[10] value at /Users/anthony/.julia/packages/MLJBase/r3heT/src/measures/measures.jl:64 [inlined]
[11] (::MLJBase.var"#264#269"{DataFrames.DataFrame,CategoricalArrays.CategoricalArray{String,1,UInt32,String,CategoricalArrays.CategoricalValue{String,UInt32},Union{}},MLJBase.UnivariateFiniteArray{Multiclass{2},String,UInt32,Float32,1}})(::MetricWrapper) at ./none:0
[12] collect(::Base.Generator{Array{Any,1},MLJBase.var"#264#269"{DataFrames.DataFrame,CategoricalArrays.CategoricalArray{String,1,UInt32,String,CategoricalArrays.CategoricalValue{String,UInt32},Union{}},MLJBase.UnivariateFiniteArray{Multiclass{2},String,UInt32,Float32,1}}}) at ./generator.jl:47
[13] (::MLJBase.var"#get_measurements#268"{Array{Tuple{Array{Int64,1},Array{Int64,1}},1},Nothing,Int64,Array{Any,1},typeof(predict),Bool,DataFrames.DataFrame,CategoricalArrays.CategoricalArray{String,1,UInt32,String,CategoricalArrays.CategoricalValue{String,UInt32},Union{}}})(::Machine{ReweighingSamplingWrapper}, ::Int64) at /Users/anthony/.julia/packages/MLJBase/r3heT/src/resampling.jl:779
[14] #248 at /Users/anthony/.julia/packages/MLJBase/r3heT/src/resampling.jl:64 [inlined]
[15] _mapreduce(::MLJBase.var"#248#249"{MLJBase.var"#get_measurements#268"{Array{Tuple{Array{Int64,1},Array{Int64,1}},1},Nothing,Int64,Array{Any,1},typeof(predict),Bool,DataFrames.DataFrame,CategoricalArrays.CategoricalArray{String,1,UInt32,String,CategoricalArrays.CategoricalValue{String,UInt32},Union{}}},Machine{ReweighingSamplingWrapper},Int64,ProgressMeter.Progress}, ::typeof(vcat), ::IndexLinear, ::UnitRange{Int64}) at ./reduce.jl:309
[16] _mapreduce_dim at ./reducedim.jl:312 [inlined]
[17] #mapreduce#584 at ./reducedim.jl:307 [inlined]
[18] mapreduce at ./reducedim.jl:307 [inlined]
[19] _evaluate!(::MLJBase.var"#get_measurements#268"{Array{Tuple{Array{Int64,1},Array{Int64,1}},1},Nothing,Int64,Array{Any,1},typeof(predict),Bool,DataFrames.DataFrame,CategoricalArrays.CategoricalArray{String,1,UInt32,String,CategoricalArrays.CategoricalValue{String,UInt32},Union{}}}, ::Machine{ReweighingSamplingWrapper}, ::CPU1{Nothing}, ::Int64, ::Int64) at /Users/anthony/.julia/packages/MLJBase/r3heT/src/resampling.jl:643
[20] evaluate!(::Machine{ReweighingSamplingWrapper}, ::Array{Tuple{Array{Int64,1},Array{Int64,1}},1}, ::Nothing, ::Nothing, ::Int64, ::Int64, ::Array{Any,1}, ::typeof(predict), ::CPU1{Nothing}, ::Bool) at /Users/anthony/.julia/packages/MLJBase/r3heT/src/resampling.jl:796
[21] evaluate!(::Machine{ReweighingSamplingWrapper}, ::CV, ::Nothing, ::Nothing, ::Int64, ::Int64, ::Array{Any,1}, ::Function, ::CPU1{Nothing}, ::Bool) at /Users/anthony/.julia/packages/MLJBase/r3heT/src/resampling.jl:859
[22] #evaluate!#242(::CV, ::Array{Any,1}, ::Array{Any,1}, ::Nothing, ::Function, ::CPU1{Nothing}, ::Nothing, ::Int64, ::Bool, ::Bool, ::Int64, ::typeof(evaluate!), ::Machine{ReweighingSamplingWrapper}) at /Users/anthony/.julia/packages/MLJBase/r3heT/src/resampling.jl:608
[23] (::MLJBase.var"#kw##evaluate!")(::NamedTuple{(:measures,),Tuple{Array{Any,1}}}, ::typeof(evaluate!), ::Machine{ReweighingSamplingWrapper}) at ./none:0
[24] #evaluate#247(::Base.Iterators.Pairs{Symbol,Array{Any,1},Tuple{Symbol},NamedTuple{(:measures,),Tuple{Array{Any,1}}}}, ::typeof(evaluate), ::ReweighingSamplingWrapper, ::DataFrames.DataFrame, ::Vararg{Any,N} where N) at /Users/anthony/.julia/packages/MLJBase/r3heT/src/resampling.jl:626
[25] (::MLJModelInterface.var"#kw##evaluate")(::NamedTuple{(:measures,),Tuple{Array{Any,1}}}, ::typeof(evaluate), ::ReweighingSamplingWrapper, ::DataFrames.DataFrame, ::Vararg{Any,N} where N) at ./none:0
[26] top-level scope at REPL[89]:1
I'm guessing that the example below failures because you assume the target is a categorical vector whose "raw" type is
Bool. However, it could be any type (in this case it isString). The example does not error if I insert the following code immediately after theunpackline:The example: