Merge pull request apache#25 from Andy-P/pull-request/f5f27779

Adds Mean Squared Error evaluation metric

src/metric.jl

@@ -113,4 +113,45 @@ function reset!(metric :: Accuracy)
   metric.n_sample = 0
 end
 
+#=doc
+.. class:: MSE
+
+   Mean Squared Error.
+
+   Calculates the mean squared error regression loss in one dimension.
+=#
+
+type MSE <: AbstractEvalMetric
+  mse_sum  :: Float64
+  n_sample :: Int
 
+  MSE() = new(0.0, 0)
+end
+
+function _update_single_output(metric :: MSE, label :: NDArray, pred :: NDArray)
+  label = copy(label)
+  pred  = copy(pred)
+
+  n_sample = size(pred)[end]
+  metric.n_sample += n_sample
+
+  for i = 1:n_sample
+    metric.mse_sum += (label[i] - pred[i])^2
+  end
+end
+
+function update!(metric :: MSE, labels :: Vector{NDArray}, preds :: Vector{NDArray})
+  @assert length(labels) == length(preds)
+  for i = 1:length(labels)
+    _update_single_output(metric, labels[i], preds[i])
+  end
+end
+
+function get(metric :: MSE)
+  return [(:MSE, metric.mse_sum / metric.n_sample)]
+end
+
+function reset!(metric :: MSE)
+  metric.mse_sum  = 0.0
+  metric.n_sample = 0
+end