From 71577542c0978c4e7174399d1a6630b40a830694 Mon Sep 17 00:00:00 2001
From: Andrey Ustyuzhanin <andrey.u@gmail.com>
Date: Mon, 13 Jul 2020 01:04:47 +0300
Subject: [PATCH] metric

---
 README.md | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/README.md b/README.md
index c9fd82c..b3ea2fe 100755
--- a/README.md
+++ b/README.md
@@ -2,3 +2,12 @@
 
 This repository will help you get started with coopetitions. The task is to modify the `solution.py`, so it stores the sum of two columns in a separate `data.predict` file into an output directory. 
 
+## Metrics
+
+Your solution will be evaluated by Mean Absolute Error metric:
+``` 
+from sklearn.metrics import mean_absolute_error
+def scorer(solution, prediction):
+    return mean_absolute_error(solution, prediction) 
+```
+It should give result as low as possible (absolute minimum is equal to zero).
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