Merge pull request #111 from jbrea/dev

fix penalize_intercept = false

Author: ablaom

src/fit/analytical.jl

@@ -24,7 +24,7 @@ function _fit(glr::GLR{L2Loss,<:L2R}, solver::Analytical, X, y, scratch)
             return augment_X(X, glr.fit_intercept) \ y
         else
             # Ridge case -- form the Hat Matrix then solve
-            H = form_XtX(X, glr.fit_intercept, λ)
+            H = form_XtX(X, glr.fit_intercept, λ, glr.penalize_intercept)
             b = X'y
             glr.fit_intercept && (b = vcat(b, sum(y)))
             return cholesky!(H) \ b

src/utils.jl

@@ -101,7 +101,7 @@ $SIGNATURES
 
 Form (X'X) while being memory aware (assuming p ≪ n).
 """
-function form_XtX(X, fit_intercept, lambda=0)
+function form_XtX(X, fit_intercept, lambda = 0, penalize_intercept = true)
     if fit_intercept
         n, p = size(X)
         XtX  = zeros(p+1, p+1)
@@ -116,7 +116,7 @@ function form_XtX(X, fit_intercept, lambda=0)
     end
     if !iszero(lambda)
         λ = convert(eltype(XtX), lambda)
-        @inbounds for i in 1:size(XtX, 1)
+        @inbounds for i in 1:size(XtX, 1) + fit_intercept * (penalize_intercept - 1)
             XtX[i,i] += λ
         end
     end

test/fit/ols-ridge-lasso-elnet.jl

@@ -22,11 +22,16 @@ end
                           scale_penalty_with_samples = false)
     rr1 = RidgeRegression(λ, penalize_intercept=true,
                              scale_penalty_with_samples = false)
+    rr2 = RidgeRegression(λ, fit_intercept = true,
+                          penalize_intercept = false,
+                          scale_penalty_with_samples = false)
 
     β_ref  = (X'X + λ*I) \ (X'y)
     β_ref1 = (X1'X1 + λ*I) \ (X1'y1)
+    β_ref2 = (X1'X1 + diagm(push!(fill(λ, p), 0))) \ (X1'y1)
     @test β_ref ≈ fit(rr, X, y)
     @test β_ref1 ≈ fit(rr1, X, y1)
+    @test β_ref2 ≈ fit(rr2, X, y1)
 
     β_cg  = fit(rr, X, y; solver=CG())
     β_cg1 = fit(rr1, X, y1; solver=CG())