implement properties for margin losses

JuliaML · Oct 6, 2016 · 0b13dbf · 0b13dbf
1 parent a00c07a
commit 0b13dbf
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Showing 2 changed files with 204 additions and 3 deletions.
diff --git a/src/supervised/margin.jl b/src/supervised/margin.jl
@@ -23,15 +23,21 @@ doc"""
 """
 immutable ZeroOneLoss <: MarginLoss end
 
-value(loss::ZeroOneLoss, target::Number, output::Number) = value(loss, target * output)
 deriv(loss::ZeroOneLoss, target::Number, output::Number) = zero(output)
 deriv2(loss::ZeroOneLoss, target::Number, output::Number) = zero(output)
 
 value{T<:Number}(loss::ZeroOneLoss, agreement::T) = sign(agreement) < 0 ? one(T) : zero(T)
 deriv{T<:Number}(loss::ZeroOneLoss, agreement::T) = zero(T)
 deriv2{T<:Number}(loss::ZeroOneLoss, agreement::T) = zero(T)
+value_deriv{T<:Number}(loss::ZeroOneLoss, agreement::T) = sign(agreement) < 0 ? (one(T), zero(T)) : (zero(T), zero(T))
 
+isminimizable(::ZeroOneLoss) = true
 isdifferentiable(::ZeroOneLoss) = false
+isdifferentiable(::ZeroOneLoss, at) = at != 0
+istwicedifferentiable(::ZeroOneLoss) = false
+istwicedifferentiable(::ZeroOneLoss, at) = at != 0
+isnemitski(::ZeroOneLoss) = true
+islipschitzcont(::ZeroOneLoss) = true
 isconvex(::ZeroOneLoss) = false
 isclasscalibrated(loss::ZeroOneLoss) = true
 isclipable(::ZeroOneLoss) = true
@@ -154,6 +160,7 @@ deriv{T<:Number}(loss::L1HingeLoss, agreement::T) = agreement >= 1 ? zero(T) : -
 deriv2{T<:Number}(loss::L1HingeLoss, agreement::T) = zero(T)
 value_deriv{T<:Number}(loss::L1HingeLoss, agreement::T) = agreement >= 1 ? (zero(T), zero(T)) : (one(T) - agreement, -one(T))
 
+isfishercons(::L1HingeLoss) = true
 isdifferentiable(::L1HingeLoss) = false
 isdifferentiable(::L1HingeLoss, at) = at != 1
 istwicedifferentiable(::L1HingeLoss) = false
@@ -197,6 +204,7 @@ deriv{T<:Number}(loss::L2HingeLoss, agreement::T) = agreement >= 1 ? zero(T) : T
 deriv2{T<:Number}(loss::L2HingeLoss, agreement::T) = agreement >= 1 ? zero(T) : T(2)
 value_deriv{T<:Number}(loss::L2HingeLoss, agreement::T) = agreement >= 1 ? (zero(T), zero(T)) : (abs2(one(T) - agreement), T(2) * (agreement - one(T)))
 
+isunivfishercons(::L2HingeLoss) = true
 isdifferentiable(::L2HingeLoss) = true
 isdifferentiable(::L2HingeLoss, at) = true
 istwicedifferentiable(::L2HingeLoss) = false
@@ -205,8 +213,8 @@ islocallylipschitzcont(::L2HingeLoss) = true
 islipschitzcont(::L2HingeLoss) = false
 islipschitzcont_deriv(::L2HingeLoss) = true
 isconvex(::L2HingeLoss) = true
-isstrictlyconvex(::L2HingeLoss) = true
-isstronglyconvex(::L2HingeLoss) = true
+isstrictlyconvex(::L2HingeLoss) = false
+isstronglyconvex(::L2HingeLoss) = false
 isclipable(::L2HingeLoss) = true
 
 # ============================================================

diff --git a/test/tst_properties.jl b/test/tst_properties.jl
@@ -317,3 +317,196 @@ end
     @test issymmetric(loss) == true
 end
 
+# --------------------------------------------------------------
+
+@testset "ZeroOneLoss" begin
+    loss = ZeroOneLoss()
+
+    @test isminimizable(loss) == true
+
+    @test isdifferentiable(loss) == false
+    @test isdifferentiable(loss, 0) == false
+    @test isdifferentiable(loss, 1) == true
+    @test istwicedifferentiable(loss) == false
+    @test istwicedifferentiable(loss, 1) == true
+
+    @test isstronglyconvex(loss) == false
+    @test isstrictlyconvex(loss) == false
+    @test isconvex(loss) == false
+
+    @test isnemitski(loss) == true
+    @test islipschitzcont(loss) == true
+    @test islocallylipschitzcont(loss) == true
+    @test isclipable(loss) == true
+    @test ismarginbased(loss) == true
+    @test isdistancebased(loss) == false
+    @test issymmetric(loss) == false
+    @test isclasscalibrated(loss) == true
+end
+
+@testset "PerceptronLoss" begin
+    loss = PerceptronLoss()
+
+    @test isminimizable(loss) == true
+
+    @test isdifferentiable(loss) == false
+    @test isdifferentiable(loss, 0) == false
+    @test isdifferentiable(loss, 1) == true
+    @test istwicedifferentiable(loss) == false
+    @test istwicedifferentiable(loss, 0) == false
+    @test istwicedifferentiable(loss, 1) == true
+
+    @test isstronglyconvex(loss) == false
+    @test isstrictlyconvex(loss) == false
+    @test isconvex(loss) == true
+
+    @test isnemitski(loss) == true
+    @test islipschitzcont(loss) == true
+    @test islocallylipschitzcont(loss) == true
+    @test isclipable(loss) == true
+    @test ismarginbased(loss) == true
+    @test isdistancebased(loss) == false
+    @test issymmetric(loss) == false
+    @test isclasscalibrated(loss) == false
+end
+
+@testset "LogitMarginLoss" begin
+    loss = LogitMarginLoss()
+
+    @test isminimizable(loss) == true
+
+    @test isdifferentiable(loss) == true
+    @test isdifferentiable(loss, 0) == true
+    @test isdifferentiable(loss, 1) == true
+    @test istwicedifferentiable(loss) == true
+    @test istwicedifferentiable(loss, 0) == true
+    @test istwicedifferentiable(loss, 1) == true
+
+    @test isstronglyconvex(loss) == false
+    @test isstrictlyconvex(loss) == true
+    @test isconvex(loss) == true
+
+    @test isnemitski(loss) == true
+    @test islipschitzcont(loss) == true
+    @test islocallylipschitzcont(loss) == true
+    @test isclipable(loss) == false
+    @test ismarginbased(loss) == true
+    @test isdistancebased(loss) == false
+    @test issymmetric(loss) == false
+    @test isclasscalibrated(loss) == true
+    @test isfishercons(loss) == true
+    @test isunivfishercons(loss) == true
+end
+
+@testset "L1HingeLoss" begin
+    loss = L1HingeLoss()
+
+    @test isminimizable(loss) == true
+
+    @test isdifferentiable(loss) == false
+    @test isdifferentiable(loss, 0) == true
+    @test isdifferentiable(loss, 1) == false
+    @test istwicedifferentiable(loss) == false
+    @test istwicedifferentiable(loss, 0) == true
+    @test istwicedifferentiable(loss, 1) == false
+
+    @test isstronglyconvex(loss) == false
+    @test isstrictlyconvex(loss) == false
+    @test isconvex(loss) == true
+
+    @test isnemitski(loss) == true
+    @test islipschitzcont(loss) == true
+    @test islocallylipschitzcont(loss) == true
+    @test isclipable(loss) == true
+    @test ismarginbased(loss) == true
+    @test isdistancebased(loss) == false
+    @test issymmetric(loss) == false
+    @test isclasscalibrated(loss) == true
+    @test isfishercons(loss) == true
+    @test isunivfishercons(loss) == false
+end
+
+@testset "L2HingeLoss" begin
+    loss = L2HingeLoss()
+
+    @test isminimizable(loss) == true
+
+    @test isdifferentiable(loss) == true
+    @test isdifferentiable(loss, 0) == true
+    @test isdifferentiable(loss, 1) == true
+    @test istwicedifferentiable(loss) == false
+    @test istwicedifferentiable(loss, 0) == true
+    @test istwicedifferentiable(loss, 1) == false
+
+    @test isstronglyconvex(loss) == false
+    @test isstrictlyconvex(loss) == false
+    @test isconvex(loss) == true
+
+    @test isnemitski(loss) == true
+    @test islipschitzcont(loss) == false
+    @test islocallylipschitzcont(loss) == true
+    @test isclipable(loss) == true
+    @test ismarginbased(loss) == true
+    @test isdistancebased(loss) == false
+    @test issymmetric(loss) == false
+    @test isclasscalibrated(loss) == true
+    @test isfishercons(loss) == true
+    @test isunivfishercons(loss) == true
+end
+
+@testset "SmoothedL1HingeLoss" begin
+    loss = SmoothedL1HingeLoss(2)
+
+    @test isminimizable(loss) == true
+
+    @test isdifferentiable(loss) == true
+    @test isdifferentiable(loss, 0) == true
+    @test isdifferentiable(loss, 1) == true
+    @test istwicedifferentiable(loss) == false
+    @test istwicedifferentiable(loss, -1) == false
+    @test istwicedifferentiable(loss, 0) == true
+    @test istwicedifferentiable(loss, 1) == false
+    @test istwicedifferentiable(loss, 2) == true
+
+    @test isstronglyconvex(loss) == false
+    @test isstrictlyconvex(loss) == false
+    @test isconvex(loss) == true
+
+    @test isnemitski(loss) == true
+    @test islipschitzcont(loss) == true
+    @test islocallylipschitzcont(loss) == true
+    @test isclipable(loss) == true
+    @test ismarginbased(loss) == true
+    @test isdistancebased(loss) == false
+    @test issymmetric(loss) == false
+    @test isclasscalibrated(loss) == true
+end
+
+@testset "ModifiedHuberLoss" begin
+    loss = ModifiedHuberLoss()
+
+    @test isminimizable(loss) == true
+
+    @test isdifferentiable(loss) == true
+    @test isdifferentiable(loss, 0) == true
+    @test isdifferentiable(loss, 1) == true
+    @test istwicedifferentiable(loss) == false
+    @test istwicedifferentiable(loss, -1) == false
+    @test istwicedifferentiable(loss, 0) == true
+    @test istwicedifferentiable(loss, 1) == false
+    @test istwicedifferentiable(loss, 2) == true
+
+    @test isstronglyconvex(loss) == false
+    @test isstrictlyconvex(loss) == false
+    @test isconvex(loss) == true
+
+    @test isnemitski(loss) == true
+    @test islipschitzcont(loss) == true
+    @test islocallylipschitzcont(loss) == true
+    @test isclipable(loss) == true
+    @test ismarginbased(loss) == true
+    @test isdistancebased(loss) == false
+    @test issymmetric(loss) == false
+    @test isclasscalibrated(loss) == true
+end
+