diff --git a/LICENSE b/LICENSE
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--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,23 @@
+Copyright (c) 2012, Kaggle
+Author: Ben Hamner (ben@benhamner.com)
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met: 
+
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer. 
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution. 
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/Metrics.cabal b/Metrics.cabal
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+++ b/Metrics.cabal
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+Name:           Metrics
+Version:        0.1.1
+Cabal-Version:  >= 1.2
+Build-Type:     Simple
+License:        BSD3
+License-File:   LICENSE
+Author:         Ben Hamner (ben@benhamner.com)
+Maintainer:     Ben Hamner (ben@benhamner.com)
+Homepage:       http://github.com/benhamner/Metrics/
+Category:       Statistics
+Synopsis:       Evaluation metrics commonly used in supervised machine learning
+Description:    Evaluation metrics commonly used in supervised machine learning
+
+Library
+    build-depends:      base >= 3 && <= 4
+                       ,hstats==0.3
+    Exposed-modules:    Metrics
diff --git a/Metrics.hs b/Metrics.hs
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+++ b/Metrics.hs
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+
+module Metrics
+    ( ae
+    , se
+    , sle
+    , mae
+    , mse
+    , msle
+    , rmse
+    , rmsle
+    , ll
+    , logLoss
+    , apk
+    , mapk
+    , auc, fstEqual, auc1, sumRank, sumEl
+    , ce
+    ) where
+
+import Data.List (groupBy, sort)
+import Math.Statistics (mean)
+
+ae :: Num a => a -> a -> a
+ae x y = abs (x-y)
+
+se :: Num a => a -> a -> a
+se x y = (x-y)^2
+
+sle :: Double -> Double -> Double
+sle x y = ((log (x+1)) - (log (y+1)))^2
+
+infinity :: Double
+infinity = -(log 0)
+
+meanZipWith :: (a -> b -> Double) -> [a] -> [b] -> Double
+meanZipWith = ((mean .) .) . zipWith
+
+meanInfZipWith :: (a -> b -> Double) -> [a] -> [b] -> Double
+meanInfZipWith f a1 a2
+    | any (==infinity) (zipWith f a1 a2) = infinity
+    | otherwise = meanZipWith f a1 a2
+
+mae :: [Double] -> [Double] -> Double
+mae = meanZipWith ae
+
+mse :: [Double] -> [Double] -> Double
+mse = meanZipWith se
+
+msle :: [Double] -> [Double] -> Double
+msle = meanZipWith sle
+
+rmse :: [Double] -> [Double] -> Double
+rmse = (sqrt .) . mse
+
+rmsle :: [Double] -> [Double] -> Double
+rmsle = (sqrt .) . msle
+
+ll :: Double -> Double -> Double
+ll 1 y = -log y
+ll 0 y = -log (1-y)
+
+logLoss :: [Double] -> [Double] -> Double
+logLoss = meanInfZipWith ll
+
+apk :: Int -> [Integer] -> [Integer] -> Double
+apk k actual predicted = (apsum actual (take k predicted) [] 0.0 0.0 0.0) / (fromIntegral (min k (length actual))) where
+    apsum _ [] _ acc _ _ = acc
+    apsum actual (p:ps) visited acc i j
+        | (elem p actual) && (not (elem p visited)) = apsum actual ps (p:visited) (acc+(i+1.0)/(j+1.0)) (i+1.0) (j+1.0) 
+        | otherwise = apsum actual ps visited acc i (j+1.0)
+
+mapk :: Int -> [[Integer]] -> [[Integer]] -> Double
+mapk k = meanZipWith (apk k)
+
+auc :: [Double] -> [Double] -> Double
+auc a p = ((sumRank a p) - (sumEl 1 a)*(((sumEl 1 a)+1)/2.0)) / ((sumEl 1 a)*(sumEl 0 a))
+
+fstEqual x y = (fst x) == (fst y)
+auc1 actual predicted = groupBy fstEqual (sort (zip predicted actual))
+sumRank actual predicted = sumRankAccum (auc1 actual predicted) 0.0 0 where
+    sumRankAccum [] rSum r = rSum
+    sumRankAccum (x:xs) rSum r = sumRankAccum xs (rSum+curPos*(r+curRank)) (r+curRank) where
+        curRank = (fromIntegral (1+(length x))) / 2.0
+        curPos = sum [1.0 | el <- x, (snd el)==1]
+sumEl el a = fromIntegral (length (filter (==el) a))
+
+ce :: Eq a => [a] -> [a] -> Double
+ce actual predicted = ((sum [1.0 | (a,p) <- (zip actual predicted), a/=p]) 
+                       / (fromIntegral (length actual)))
+
diff --git a/Setup.hs b/Setup.hs
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+++ b/Setup.hs
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+import Distribution.Simple
+main = defaultMain