diff --git a/index.html b/index.html
index 3a5501d..5b7b9a1 100644
--- a/index.html
+++ b/index.html
@@ -699,15 +699,17 @@ NN.Network.Stochastic = function(inNetwork, inTrainingSet, inIterations)
         [ 0.99, 0.85],
         [ 1.2,  1.05]
     ];
+	let goals = [
+        [1, 1, 0],
+        [0, 0, 1]
+    ];
 
     var layer1 = NN.Layer.Create(1, 1);
     layer1.Forward.Matrix = matrix1;
 
-    var layer2 = NN.Layer.Create(1, 1);
-    layer2.Forward.Matrix = matrix2;
-
     let stage1 = NN.Layer.Forward(layer1, typeA);
+	let stage1Error = NN.Layer.Error(layer1, goals);
 
-    console.log(stage1);
+    console.log(stage1Error);
 
 </script>
\ No newline at end of file
diff --git a/nn.test.js b/nn.test.js
index f86af35..96de2aa 100644
--- a/nn.test.js
+++ b/nn.test.js
@@ -19,17 +19,14 @@ let typeB = [
 
 Deno.test("check.forward", ()=>
 {
-    let training = [];
-    let stages = [];
-    let layers = [
-        [
-            [-0.43662948305036675, -0.368590640707799, -0.23227179558890843],
-            [-0.004292653969505622, 0.38670055222186317, -0.2478421495365568],
-            [0.738181366836224, 0.3389203747353555, 0.4920200816404332]
-        ],
-        [
-            [0.5793881115472015, 0.9732593374796092, 0.15207639877016987, -0.5356575655337803]
-        ]
+    let matrix1 = [
+    [-0.43662948305036675, -0.368590640707799, -0.23227179558890843],
+    [-0.004292653969505622, 0.38670055222186317, -0.2478421495365568],
+    [0.738181366836224, 0.3389203747353555, 0.4920200816404332]
+    ];
+
+    let matrix2 = [
+    [0.5793881115472015, 0.9732593374796092, 0.15207639877016987, -0.5356575655337803]
     ];
 
     let typeA = [
@@ -40,11 +37,14 @@ Deno.test("check.forward", ()=>
         [ 0.99, 0.85],
         [ 1.2,  1.05]
     ];
+    let goals = [
+        [1, 1, 0],
+        [0, 0, 1]
+    ];
 
-    Label(training, typeA, [1]);
-    stages.push(training[0]);
-    Forward(stages, layers);
-    console.log(stages);
+    let layers = [matrix1];
+    let stages = Forward(Methods.Mutate.Pad(typeA), layers);
+    Backward(stages, layers, goals, 0.1);
 });
 
 /*
diff --git a/nn.ts b/nn.ts
index d902636..874b28f 100644
--- a/nn.ts
+++ b/nn.ts
@@ -16,22 +16,25 @@ const Label = (inSet:any, inData:Cloud.M, inLabel:Cloud.V):N =>
     return inSet;
 };
 
-const Forward = (inStages:N, inLayers:N):Cloud.M =>
+const Forward = (inData:Cloud.M, inLayers:N):N =>
 {
     let i:number;
-    let process = (index:number):Cloud.M => M.Batch.Sigmoid(M.Batch.Affine(inStages[index], inLayers[index]));
+    let stages = [inData];
+    let process = (index:number):Cloud.M => M.Batch.Sigmoid(M.Batch.Affine(stages[index], inLayers[index]));
 
     for(i=0; i<inLayers.length-1; i++)
     {
-        inStages[i+1] = M.Mutate.Pad(process(i));
+        stages[i+1] = M.Mutate.Pad(process(i));
     }
-    inStages[i+1] = process(i);
-    return inStages[i+1];
+    stages[i+1] = process(i);
+    return stages;
 };
 const Backward = (inStages:N, inLayers:N, inGoals:Cloud.M, inRate:number):N =>
 {
     let i:number;
-    let errorBack:Cloud.M = M.Batch.Subtract(Forward(inStages, inLayers), inGoals);
+    let errorBack:Cloud.M = M.Batch.Subtract(inStages[inStages.length-1], inGoals);
+
+    console.log(errorBack);
 
     for(i=inLayers.length-1; i>=0; i--)
     {