Ticket #1390: blatt2a6.hs

data Class = A | B deriving (Eq, Show)
type Coord = (Double, Double)
type Neuron = (Double, Double, Double)
type Merk   = (Coord, Class)

merk1 :: [Merk]
merk1 = [
        ((0.1, 0.4), A),
        ((0.6, 0.1), A),
        ((0.2, 1.0), B),
        ((0.8, 0.9), B)
        ]

merk2 :: [Merk]
merk2 = [
        ((0.1, 1.0), B),
        ((0.1, 0.1), A),
        ((0.3, 0.3), B),
        ((0.5, 0.9), A)
        ]

addN :: Neuron -> Neuron -> Neuron
(w1,w2,b) `addN` (w1',w2',b') = (w1 + w1', w2 + w2', b + b')

guess :: Neuron -> Coord -> Class
guess (w1, w2, b) (x1,x2) =  if w1*x1 + w2*x2 > b then B else A

errors :: Neuron -> [Merk] -> [Merk]
errors n = filter (\(co, cl) -> guess n co /= cl)

iteration :: [Merk] -> Neuron -> Neuron
iteration merks n@(w1,w2,b) = foldr addN n $ map delta $ errors n merks
  where delta ((x1,x2), c) = (dir c * x1, dir c * x2, dir c * 1)
        dir A =  1
        dir B = -1      

startn :: Neuron
startn = (-1, 1, 0)

pretty :: Neuron -> [Merk] -> IO ()
pretty n merks = do
        putStrLn $ concat $ map printLine (zip steps [0..]) 
        putStrLn $ "Ergebnis "++(show res)
  where (steps,res:_) = span (\n -> not (null (errors n merks))) $ iterate (iteration merks) n
        printLine (step,i) = "Schritt "++ (show i) ++ ": " ++ (show step) ++
                                " (Falsch: "++ show ((errors step merks)) ++ ")"