diff --git a/CSVParser.hs b/CSVParser.hs
index 0fd325d..2027677 100644
--- a/CSVParser.hs
+++ b/CSVParser.hs
@@ -1,31 +1,31 @@
 module CSVParser (
-	parseCSV
-)where
+    parseCSV
+    )where
 
 import Text.ParserCombinators.Parsec
 
 csvFile :: GenParser Char st [[String]]
 csvFile = do
-	result <- many line
-	eof
-	return result
+    result <- many line
+    eof
+    return result
 
 line :: GenParser Char st [String]
 line = do
-	result <- cells
-	_ <- eol
-	return result
+    result <- cells
+    _ <- eol
+    return result
 
 cells :: GenParser Char st [String]
 cells = do
-	first <- cellContent
-	next <- remainingCells
-	return (first : next)
+    first <- cellContent
+    next <- remainingCells
+    return (first : next)
 
 remainingCells :: GenParser Char st [String]
 remainingCells =
-	(char ',' >> cells)            -- Found comma?  More cells coming
-	<|> return []                -- No comma?  Return [], no more cells
+    (char ',' >> cells)            -- Found comma?  More cells coming
+    <|> return []                -- No comma?  Return [], no more cells
 
 cellContent :: GenParser Char st String
 cellContent = many (noneOf ",\n")
diff --git a/DataModel.hs b/DataModel.hs
index eff9c54..7ce2e48 100644
--- a/DataModel.hs
+++ b/DataModel.hs
@@ -8,31 +8,44 @@ type Frequency = Double
 type Confidence = Double
 
 class Freq a where
-	frequency :: [ItemSet] -> a -> Frequency
+    frequency :: [ItemSet] -> a -> Frequency
 
 data Item = Item String deriving (Eq, Ord)
+
 instance Show Item where
-	show (Item s) = s --"Item " ++ s
+    show (Item a) = a
+
 
 data ItemSet = ItemSet (Set Item) deriving (Eq, Ord)
 
 instance Show ItemSet where
-	show (ItemSet x) = foldr ((\y old -> y ++ " " ++ old).show) "" (Set.toList x)
+    show (ItemSet x) =
+        init $ foldr ((\y old -> y ++ " " ++ old).show) "" (Set.toList x)
 
 instance Freq ItemSet where
-	frequency table (ItemSet set) = setCount / fromIntegral (length table) where
-		setCount = fromIntegral $ count table (ItemSet set)
+    frequency table (ItemSet set) =
+        setCount / fromIntegral (length table) where
+            setCount = fromIntegral $ count table (ItemSet set)
 
 count :: [ItemSet] -> ItemSet -> Count
-count table (ItemSet set) = length (filter (\(ItemSet row) -> set `Set.isSubsetOf` row) table)
+count table (ItemSet set) =
+    length (filter isSuperset table) where
+        isSuperset (ItemSet row) = set `Set.isSubsetOf` row
+
+difference :: ItemSet -> ItemSet -> ItemSet
+difference (ItemSet set1) (ItemSet set2) = ItemSet (Set.difference set1 set2)
+
+empty :: ItemSet
+empty = ItemSet (Set.fromList [])
 
 data Rule = Rule ItemSet ItemSet deriving (Eq)
 
 instance Show Rule where
-	show (Rule a b) = show a ++ "-> " ++ show b
+    show (Rule a b) = show a ++ "->" ++ show b
 
 instance Freq Rule where
-	frequency table (Rule (ItemSet set1) (ItemSet set2)) = frequency table $ ItemSet (set1 `Set.union` set2)
+    frequency table (Rule (ItemSet set1) (ItemSet set2)) = frequency table $
+        ItemSet (set1 `Set.union` set2)
 
 confidence :: [ItemSet] -> Rule -> Confidence
 confidence table (Rule x y) = frequency table (Rule x y) / frequency table x
diff --git a/ExtractRules.hs b/ExtractRules.hs
new file mode 100644
index 0000000..50b3727
--- /dev/null
+++ b/ExtractRules.hs
@@ -0,0 +1,32 @@
+module ExtractRules (
+    extractRules
+) where
+import DataModel
+import qualified Data.Set as Set
+import qualified Data.Map as Map
+import Data.Map(Map)
+
+extractRules :: Confidence -> [ItemSet] -> [Rule]
+extractRules threshold patterns = filter (\x -> threshold <= confidence patterns x) rules where
+    rules = Map.foldrWithKey (\k v old -> ruleFromSubset v k : old) [] subsets
+    subsets = foldr (\x old -> insertMultiple (filteredPowerset x) x old) Map.empty patterns
+    filteredPowerset (ItemSet set) = map (ItemSet . Set.fromList) $
+        filter (\val -> val /= Set.toList set && val /= []) $ powerset $ Set.toList set
+
+ruleFromSubset :: ItemSet -> ItemSet -> Rule
+ruleFromSubset set subset = Rule subset (difference set subset)
+
+
+
+insertMultiple :: Ord k => [k] -> a -> Map k a -> Map k a
+insertMultiple keys value m = foldr (\x old -> Map.insert x value old) m keys
+
+powerset :: [a] -> [[a]]
+powerset []     = [[]]
+powerset (x:xs) = xss /\/ map (x:) xss where
+    xss = powerset xs
+
+(/\/) :: [a] -> [a] -> [a]
+[]     /\/ ys = ys
+(x:xs) /\/ ys = x : (ys /\/ xs)
+
diff --git a/FreqParser.hs b/FreqParser.hs
new file mode 100644
index 0000000..62a8a1d
--- /dev/null
+++ b/FreqParser.hs
@@ -0,0 +1,11 @@
+module ItemsParser (
+    parseItems,
+    parseItemsWithFreq
+    )where
+import qualified Data.Map as Map
+import Data.Map(Map)
+import DataModel
+
+parseItems :: String -> Either ParseError [ItemSet]
+
+parseItemsWithFreq :: String -> Either ParseError Map ItemSet Frequency
diff --git a/FrequentPatterns.hs b/FrequentPatterns.hs
index 1ee7eeb..891a14d 100644
--- a/FrequentPatterns.hs
+++ b/FrequentPatterns.hs
@@ -1,15 +1,18 @@
 module FrequentPatterns (
-	frequentPatterns
-)	where
+    frequentPatterns
+    ) where
 import DataModel
 import qualified Data.Set as Set
-import Debug.Trace (traceShow)
+import Debug.Trace (trace)
 import qualified Data.List as List
 
 semiUnion :: ItemSet -> ItemSet -> ItemSet
-semiUnion (ItemSet set1) (ItemSet set2) = ItemSet (if max1 <= max2 && Set.delete max1 set1 == Set.delete max2 set2 then set1 `Set.union` set2 else Set.empty) where
-	max1 = Set.findMax set1
-	max2 = Set.findMax set2
+semiUnion (ItemSet set1) (ItemSet set2) = ItemSet $
+    if max1 <= max2 && Set.delete max1 set1 == Set.delete max2 set2
+    then set1 `Set.union` set2
+    else Set.empty where
+        max1 = Set.findMax set1
+        max2 = Set.findMax set2
 
 -- generate all possible combinations from a set of singletons
 -- generateLevels :: [Item] -> [[ItemSet]]
@@ -19,15 +22,19 @@ semiUnion (ItemSet set1) (ItemSet set2) = ItemSet (if max1 <= max2 && Set.delete
 
 -- generate the next level in a bottom-up route
 generateNextLevel :: [ItemSet] -> [ItemSet]
-generateNextLevel level = traceShow ("Computing level " ++ show (isSize (head level))) $ foldr (\value old -> generate value ++ old) [] level where
-	generate value = takeWhile (/= empty) (foldr (\x old -> semiUnion value x : old) [] (tail $ List.dropWhile (/= value) level))
-	empty = ItemSet $ Set.fromList []
-	isSize (ItemSet set) = Set.size set
+generateNextLevel level = trace ("Computing level " ++ show (isSize (head level))) $
+    foldr (\value old -> generate value ++ old) [] level where
+        generate value = takeWhile (/= empty)
+            (foldr (\x old -> semiUnion value x : old) [] (tail $ List.dropWhile (/= value) level))
+        isSize (ItemSet set) = Set.size set
 
 singletons :: [ItemSet] -> [Item]
-singletons table = Set.toList $ foldr (\(ItemSet row) old -> old `Set.union` row) (Set.fromList []) table where
+singletons table = Set.toList $ foldr union (Set.fromList []) table where
+	union (ItemSet row) old = old `Set.union` row
 
 frequentPatterns :: Frequency -> [ItemSet] -> [[ItemSet]]
-frequentPatterns thresh table = until (\x -> [] == head x) (\x -> filterByFrequency (generateNextLevel (head x)) : x) [firstLevel] where
-	firstLevel = filterByFrequency $ map (\x -> ItemSet $ Set.fromList [x]) (singletons table)
-	filterByFrequency = filter (\x -> frequency table x >= thresh)
+frequentPatterns thresh table = until (\x -> [] == head x)
+    (\x -> filterByFrequency (generateNextLevel (head x)) : x) [firstLevel] where
+        firstLevel = filterByFrequency $ map (\x -> ItemSet $ Set.fromList [x]) $
+            trace "Generated Singletons" (singletons table)
+        filterByFrequency = filter (\x -> frequency table x >= thresh)
diff --git a/phase1.hs b/phase1.hs
index 74eb09d..500617a 100644
--- a/phase1.hs
+++ b/phase1.hs
@@ -7,12 +7,22 @@ import Control.Monad(when)
 
 main :: IO()
 main = do
-	args <- getArgs
-	when (2 /= length args) (error "Usage: Main <file.csv> <threshold>")
-	let filename = head args
-	let threshold = read $ last args
-	file <- readFile filename
-	case parseCSV file of
-		Left _ -> error "Could not parse out.csv"
-		Right val -> mapM_ (\x -> putStrLn (show x ++ "(" ++ show (count table x) ++ ")")) (concat (frequentPatterns threshold table)) where
-			table = map (ItemSet. Set.fromList .map Item) val
+    args <- getArgs
+    when (2 > length args)
+        (error "Usage: Main <table.csv> <threshold> <outfile.csv>")
+    let filename = head args
+    let threshold = read $ args !! 1
+    file <- readFile filename
+    case parseCSV file of
+        Left _ -> error "Could not parse out.csv"
+        Right val -> do
+            let table = map (ItemSet. Set.fromList .map Item) val
+            let freqPats = concat (frequentPatterns threshold table)
+	    let output = formatToCSV table freqPats
+	    putStrLn output
+            when (length args > 2) $
+                writeFile (args !! 2) $ output
+
+formatToCSV :: [ItemSet] -> [ItemSet] -> String
+formatToCSV table frequents = foldr (\x old -> old ++ formatRow x ++ "\n") "" frequents where
+    formatRow (ItemSet set) = init $ Set.foldr (\x old -> old ++ show x ++ ",") (show (count table (ItemSet set)) ++",") set
diff --git a/phase2.hs b/phase2.hs
new file mode 100644
index 0000000..7240594
--- /dev/null
+++ b/phase2.hs
@@ -0,0 +1,19 @@
+import CSVParser
+import DataModel
+import ExtractRules
+import qualified Data.Set as Set
+import System.Environment(getArgs)
+import Control.Monad(when)
+
+main :: IO()
+main = do
+    args <- getArgs
+    when (2 /= length args) (error "Usage: phase2 <file.csv> <threshold>")
+    let filename = head args
+    let threshold = read $ last args
+    file <- readFile filename
+    case parseCSV file of
+        Left _ -> error "Could not parse out.csv"
+        Right val -> do
+            let table = map (ItemSet. Set.fromList .map Item) val
+            print $ extractRules threshold table