getting nicer

1 files changed, 2 insertions, 3 deletions

diff --git a/mnist/Neuronet.hs b/mnist/Neuronet.hs
index e3344c7..ece288a 100644
--- a/mnist/Neuronet.hs
+++ b/mnist/Neuronet.hs
@@ -24,7 +24,7 @@ module Neuronet
      ,backprop
     )where
 
-import Numeric.LinearAlgebra (Matrix,Vector,tr,scale,cmap,(#>),randn,toList,fromList,toLists,fromLists,Container)
+import Numeric.LinearAlgebra (Matrix,Vector,tr,scale,cmap,(#>),randn,toList,fromList,toLists,fromLists,outer)
 import Data.List
 
 -- | A layer of our network consists of a weight matrix with input weights 
@@ -58,10 +58,9 @@ asknet net x = snd . last $ wghtact net x
 -- split in the weight and bias partial derivatives respectively). 
 -- Keep the required assumptions about the cost function in mind!
 backprop :: Neuronet -> Vector Double -> Vector Double -> [(Matrix Double,Vector Double)]
-backprop net x y = zipWith (\a e->(wm a e,e)) (x:map snd wa) (go $ zip ws wa)
+backprop net x y = zipWith (\a e->(outer e a,e)) (x:map snd wa) (go $ zip ws wa)
     where ws = (++[fromLists []]) . tail . map fst $ net
           wa = wghtact net x
-          wm a e = fromLists $ map (\e->map (*e) (toList a)) (toList e)
           go [(w,(z,a))] = [cost_derivative a y * cmap sigmoid' z]
           go ((w,(z,a)):lx) =let r@(e:_)=go lx in tr w #> e * cmap sigmoid' z:r