closes #71

Author: tlienart

src/mlj/interface.jl

@@ -55,7 +55,12 @@ function MMI.fit(m::Union{CLF_MODELS...}, verb::Int, X, y)
     else
         c = nclasses
     end
-    clf    = glr(m)
+    clf = glr(m)
+    # allow logclf to become multiclf
+    if m isa LogisticClassifier
+        m.multi_class = c > 1
+    end
+
     solver = m.solver === nothing ? _solver(clf, size(Xmatrix)) : m.solver
     # get the parameters
     θ = fit(clf, Xmatrix, yplain, solver=solver)

src/utils.jl

@@ -4,7 +4,7 @@ $SIGNATURES
 Return nothing if the number of rows of `X` and `y` match and throws a
 `DimensionMismatch` error otherwise.
 """
-function check_nrows(X::Matrix, y::VecOrMat)::Nothing
+function check_nrows(X::AbstractMatrix, y::AbstractVecOrMat)::Nothing
     size(X, 1) == size(y, 1) && return nothing
     throw(DimensionMismatch("`X` and `y` must have the same number of rows."))
 end
@@ -21,7 +21,7 @@ $SIGNATURES
 
 Given a matrix `X`, append a column of ones if `fit_intercept` is true.
 """
-function augment_X(X::Matrix{<:Real}, fit_intercept::Bool)
+function augment_X(X::AbstractMatrix{<:Real}, fit_intercept::Bool)
     fit_intercept || return X
     return hcat(X, ones(eltype(X), size(X, 1)))
 end

test/interface/fitpredict.jl

@@ -67,3 +67,13 @@ end
     @test gr isa GLR
     @test gr.penalty isa ScaledPenalty{L1Penalty}
 end
+
+# see issue #71
+@testset "Logistic-m" begin
+    X, y = MLJBase.make_blobs(centers=3)
+    model = LogisticClassifier()
+    mach = MLJBase.machine(model, X, y)
+    fit!(mach)
+    fp = MLJBase.fitted_params(mach)
+    @test unique(fp.classes) == [1,2,3]
+end