Added Chapter 8

This commit is contained in:
Nishant Shukla 2014-06-21 12:03:14 -04:00
parent 797db94d9e
commit ac0af15815
36 changed files with 1005 additions and 1 deletions

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-- Initial Code0801.cabal generated by cabal init. For further
-- documentation, see http://haskell.org/cabal/users-guide/
name: Code0801
version: 0.1.0.0
synopsis: Implementing k-means.
-- description:
homepage: haskelldata.com
license: GPL-2
license-file: ../LICENSE
author: Nishant Shukla
maintainer: nick722@gmail.com
-- copyright:
category: Clustering
build-type: Simple
-- extra-source-files:
cabal-version: >=1.10
executable Code0801
main-is: Main.hs
-- other-modules:
-- other-extensions:
build-depends: base >=4.6 && <4.7, containers >=0.5 && <0.6
-- hs-source-dirs:
default-language: Haskell2010

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import Data.Map (Map)
import qualified Data.Map as Map
import Data.List (minimumBy, sort, transpose)
import Data.Ord (comparing)
type Point = [Double]
-- Euclidian distance function
dist :: Point -> Point -> Double
dist a b = sqrt $ sum $ map (^2) $ zipWith (-) a b
-- Assign points to closest centroids
assign :: [Point] -> [Point] -> Map Point [Point]
assign centroids points = Map.fromListWith (++)
[(assignPoint p, [p]) | p <- points]
where assignPoint p = minimumBy (comparing (dist p)) centroids
-- Relocate centroids to the middle of its group
relocate :: Map Point [Point] -> Map Point [Point]
relocate centroidsMap = Map.foldWithKey insertCenter Map.empty centroidsMap
where insertCenter _ ps m = Map.insert (center ps) ps m
center [] = [0,0]
center ps = map average (transpose ps)
average xs = sum xs / fromIntegral (length xs)
-- Assign points and relocate centroids until centroids converge
kmeans :: [Point] -> [Point] -> [Point]
kmeans centroids points =
if converged then centroids else kmeans (Map.keys newCentroidsMap) points
where converged = all (< 0.00001) $
zipWith dist (sort centroids) (Map.keys newCentroidsMap)
newCentroidsMap = relocate (assign centroids points)
equal a b = dist a b < 0.00001
-- Run the kmeans algorithm on test points
main = do
let points = [[0,0], [1,0], [0,1], [1,1], [7,5], [9,6], [8,7]]
let centroids = kmeans (take 2 points) points
print centroids -- [[0.5,0.5],[8.0,6.0]]

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default:
cabal install --bindir=./
clean:
rm -rf dist Setup.hs Code0801 *~

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-- Initial Code0802.cabal generated by cabal init. For further
-- documentation, see http://haskell.org/cabal/users-guide/
name: Code0802
version: 0.1.0.0
synopsis: Implementing hierarchical clustering.
-- description:
homepage: haskelldata.com
license: GPL-2
license-file: ../LICENSE
author: Nishant Shukla
maintainer: nick722@gmail.com
-- copyright:
category: Clustering
build-type: Simple
-- extra-source-files:
cabal-version: >=1.10
executable Code0802
main-is: Main.hs
-- other-modules:
-- other-extensions:
build-depends: base >=4.6 && <4.7, containers >=0.5 && <0.6
-- hs-source-dirs:
default-language: Haskell2010

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Ch08/Code02_hier/Main.hs Normal file
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import Data.Map (Map, (!), delete)
import qualified Data.Map as Map
import Data.Ord (comparing)
import Data.List (sort, tails, transpose, minimumBy)
type Point = [Double]
center :: [Point] -> Point
center points = map average (transpose points)
where average xs = sum xs / fromIntegral (length xs)
merge :: Map Point [Point] -> Map Point [Point]
merge m = Map.insert (center [a,b]) ((m ! a) ++ (m ! b)) newM
where (a,b) = nearest (Map.keys m)
newM = Map.delete b (Map.delete a m)
equal a b = dist a b < 0.00001
dist a b = sqrt $ sum $ map (^2) $ zipWith (-) a b
nearest points = minimumBy (comparing (uncurry dist))
[(a, b) | (a : rest) <- tails points, b <- rest]
run :: Int -> Map Point [Point] -> Map Point [Point]
run k m = if length (Map.keys m) == k then m else run k (merge m)
initilize :: [Point] -> Map Point [Point]
initilize points = foldl (\m p -> Map.insert p [p] m) Map.empty points
-- Running heiarchical clustering
main = do
let points = [[0,0], [1,0], [0,1], [1,1], [7,5], [9,6], [8,7]]
let centroids = Map.keys $ run 2 (initilize points)
print centroids

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default:
cabal install --bindir=./
clean:
rm -rf dist Setup.hs Code0802 *~

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-- Initial Code0803.cabal generated by cabal init. For further
-- documentation, see http://haskell.org/cabal/users-guide/
name: Code0803
version: 0.1.0.0
synopsis: Hierarchical clustering library.
-- description:
homepage: haskelldata.com
license: GPL-2
license-file: ../LICENSE
author: Nishant Shukla
maintainer: nick722@gmail.com
-- copyright:
category: Clustering
build-type: Simple
-- extra-source-files:
cabal-version: >=1.10
executable Code0803
main-is: Main.hs
-- other-modules:
-- other-extensions:
build-depends: base >=4.6 && <4.7, hierarchical-clustering >=0.4 && <0.5
-- hs-source-dirs:
default-language: Haskell2010

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import Data.Clustering.Hierarchical
data Point = Point [Double] deriving Show
dist :: Point -> Point -> Distance
dist (Point a) (Point b) = sqrt $ sum $ map (^2) $ zipWith (-) a b
-- Using hiearchical clustering from a library
main = do
let points = map Point [[0,0], [1,0], [0,1], [1,1], [7,5], [9,6], [8,7]]
let clusters = dendrogram SingleLinkage points dist
printCluster clusters 2.0
printCluster :: Dendrogram Point -> Double -> IO ()
printCluster clusters cut = do
let es = map elements $ clusters `cutAt` cut
mapM_ print es

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default:
cabal install --bindir=./
clean:
rm -rf dist Setup.hs Code0803 *~

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-- Initial Code0804.cabal generated by cabal init. For further
-- documentation, see http://haskell.org/cabal/users-guide/
name: Code0804
version: 0.1.0.0
synopsis: Finding number of clusters.
-- description:
homepage: haskelldata.com
license: GPL-2
license-file: ../LICENSE
author: Nishant Shukla
maintainer: nick722@gmail.com
-- copyright:
category: Clustering
build-type: Simple
-- extra-source-files:
cabal-version: >=1.10
executable Code0804
main-is: Main.hs
-- other-modules:
-- other-extensions:
build-depends: base >=4.6 && <4.7, containers >=0.5 && <0.6, random >=1.0 && <1.1, statistics >=0.11 && <0.12, vector >=0.10 && <0.11
-- hs-source-dirs:
default-language: Haskell2010

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import Data.Map (Map, (!), keys)
import qualified Data.Map as Map
import Data.List (sort, and, minimumBy)
import Data.Ord (comparing)
import Data.Maybe (fromJust)
import System.Random
import Statistics.Sample (variance)
import Data.Vector.Unboxed (fromList)
type Point = [Double]
-- Euclidian distance function
dist :: Point -> Point -> Double
dist a b = sqrt $ sum $ map (^2) $ zipWith (-) a b
-- Assign points to closest centroids
assign :: [Point] -> [Point] -> Map Point [Point]
assign centroids points = Map.fromListWith (++)
[(assignPoint p, [p]) | p <- points]
where assignPoint p = minimumBy (comparing (dist p)) centroids
-- Relocate centroids to the middle of its group
relocate :: Map Point [Point] -> Map Point [Point]
relocate centroidsMap = Map.foldWithKey insertCenter Map.empty centroidsMap
where insertCenter _ ps m = Map.insert (center ps) ps m
center [] = [0,0]
center points = map (/len) $ foldl1 add points
where len = fromIntegral $ length points
add = zipWith (+)
-- Assign points and relocate centroids until centroids converge
kmeans :: [Point] -> [Point] -> [Point]
kmeans centroids points =
if converged then centroids else kmeans (Map.keys newCentroidsMap) points
where converged = all (< 0.00001) $
zipWith dist (sort centroids) (Map.keys newCentroidsMap)
converged' = and $ zipWith equal
(sort centroids) (sort (Map.keys newCentroidsMap))
newCentroidsMap = relocate (assign centroids points)
equal a b = dist a b < 0.00001
-- Run the kmeans algorithm on test points
main = do
let points = [[0,0], [1,0], [0,1], [20,0], [21,0], [20,1], [40,5], [40,6], [40,8]]
let centroids = [kmeans (take k points) points | k <- [1..length points]]
print centroids
let avgVars = map (avgVar points) centroids
print avgVars
-- Compute the average variance
avgVar points centroids = avg [variance . fromList $
map (dist c) ps | (c, ps) <- Map.assocs m]
where m = assign centroids points
avg xs = (sum xs) / (fromIntegral (length xs))

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default:
cabal install --bindir=./
clean:
rm -rf dist Setup.hs Code0804 *~

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default:
wget -N https://github.com/BinRoot/lexeme-clustering/archive/master.zip
clean:
rm -rf master.zip *~

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git clone https://github.com/kawu/lexeme-clustering.git
cd lexeme-clustering/
cabal install
emacs input.txt &
mama
papa
sissy
bro
mother
father
grandfather
grandmother
uncle
mommy
daddy
ma
pa
mom
dad
sister
brother
dist/build/lexeme-clustering/lexeme-clustering input.txt
# Clustering
bro, brother
dad, daddy
grandfather, grandmother
father, ma, mama, mom, mommy, mother, pa, papa
sissy, sister
uncle

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-- Initial Code0806.cabal generated by cabal init. For further
-- documentation, see http://haskell.org/cabal/users-guide/
name: Code0806
version: 0.1.0.0
synopsis: Classifying parts of speech.
-- description:
homepage: haskelldata.com
license: GPL-2
license-file: ../LICENSE
author: Nishant Shukla
maintainer: nick722@gmail.com
-- copyright:
category: Classifying
build-type: Simple
-- extra-source-files:
cabal-version: >=1.10
executable Code0806
main-is: Main.hs
-- other-modules:
-- other-extensions:
build-depends: base >=4.6 && <4.7, chatter >=0.1 && <0.2, text >=0.11 && <0.12
-- hs-source-dirs:
default-language: Haskell2010

9
Ch08/Code06_pos/Main.hs Normal file
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import NLP.POS
import Data.Text (pack)
-- Tagging the parts of speech
main = do
tagger <- defaultTagger
let text = pack "The best jokes have no punchline."
print $ tag tagger text

5
Ch08/Code06_pos/Makefile Normal file
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default:
cabal install --bindir=./
clean:
rm -rf dist Setup.hs Code0806 *~

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default:
wget -N http://hackage.haskell.org/package/sequor-0.7.2/sequor-0.7.2.tar.gz
clean:
rm -rf sequor* *~

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On
Tuesday
Richard
Stallman
will
visit
Charlottesville
,
Virginia
in
the
United
States

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O
B-DATE
B-PERSON
I-PERSON
O
O
B-GPE:CITY
O
B-GPE:STATE_PROVINCE
O
O
B-GPE:COUNTRY
I-GPE:COUNTRY

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default:
cabal install --bindir=./
clean:
rm -rf dist Setup.hs Code0801 *~

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$ cabal install sequor --prefix=`pwd`
command: train
template-file: data/all.features
train-file: data/train.conll
model-file: model
learning rate: 0.1
beam size: 10
number of iteration: 5
minimum feature frequency for label dictionary: 100
path to heldout data: data/devel.conll
use hasing instead of feature dictionary
$ ./bin/sequor train data/all.features data/train.conll model --rate 0.1 --beam 10 --iter 5 --hash --heldout data/devel.conll
$ ./bin/sequor predict model < data/test.conll > data/test.labels

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-- Initial Code0413.cabal generated by cabal init. For further
-- documentation, see http://haskell.org/cabal/users-guide/
name: Code0809
version: 0.1.0.0
synopsis: Implementing a decision tree.
-- description:
homepage: haskelldata.com
license: GPL-2
license-file: ../LICENSE
author: Nishant Shukla
maintainer: nick722@gmail.com
-- copyright:
category: Data
build-type: Simple
-- extra-source-files:
cabal-version: >=1.10
executable Code0809
main-is: Main.hs
-- other-modules:
-- other-extensions:
build-depends: base >=4.6 && <4.7, containers >=0.5 && <0.6, csv >=0.1 && <0.2
-- hs-source-dirs:
default-language: Haskell2010

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import Data.List (nub, elemIndices)
import qualified Data.Map as M
import Data.Map (Map, (!))
import Data.List (transpose)
import Text.CSV
type Class = String
type Feature = String
type Entropy = Double
type DataSet = [([String], Class)]
-- Classifying a dataset using a decision tree
main = do
rawCSV <- parseCSVFromFile "input.csv"
either handleError doWork rawCSV
handleError = error "invalid file"
doWork csv = do
let removeInvalids = filter (\x -> length x > 1)
let myData = map (\x -> (init x, last x)) $ removeInvalids csv
print $ dtree "root" myData
samples :: DataSet -> [[String]]
samples d = map fst d
classes :: DataSet -> [String]
classes d = map snd d
entropy :: (Eq a) => [a] -> Entropy
entropy xs = sum $ map (\x -> prob x * info x) $ nub xs
where prob x = (length' (elemIndices x xs)) / (length' xs)
info x = negate $ logBase 2 (prob x)
length' xs = fromIntegral $ length xs
splitAttr :: [(Feature, Class)] -> Map Feature [Class]
splitAttr fc = foldl (\m (f,c) -> M.insertWith (++) f [c] m) M.empty fc
splitEntropy :: Map Feature [Class] -> M.Map Feature Entropy
splitEntropy m = M.map entropy m
informationGain :: [Class] -> [(Feature, Class)] -> Double
informationGain s a = entropy s - newInformation
where eMap = splitEntropy $ splitAttr a
m = splitAttr a
toDouble x = read x :: Double
ratio x y = (fromIntegral x) / (fromIntegral y)
sumE = M.map (\x -> (fromIntegral.length) x / (fromIntegral.length) s) m
newInformation = M.foldWithKey (\k a b -> b + a*(eMap!k)) 0 sumE
highestInformationGain :: DataSet -> Int
highestInformationGain d = snd $ maximum $
zip (map ((informationGain . classes) d) attrs) [0..]
where attrs = map (attr d) [0..s-1]
attr d n = map (\(xs,x) -> (xs!!n,x)) d
s = (length . fst . head) d
data DTree = DTree { feature :: String
, children :: [DTree] }
| Node String String
deriving Show
datatrees :: DataSet -> Map String DataSet
datatrees d =
foldl (\m (x,n) -> M.insertWith (++) (x!!i) [((x `dropAt` i), fst (cs!!n))] m)
M.empty (zip (samples d) [0..])
where i = highestInformationGain d
dropAt xs i = let (a,b) = splitAt i xs in a ++ drop 1 b
cs = zip (classes d) [0..]
allEqual :: Eq a => [a] -> Bool
allEqual [] = True
allEqual [x] = True
allEqual (x:xs) = x == (head xs) && allEqual xs
dtree :: String -> DataSet -> DTree
dtree f d
| allEqual (classes d) = Node f $ head (classes d)
| otherwise = DTree f $ M.foldWithKey (\k a b -> b ++ [dtree k a] ) [] (datatrees d)

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default:
cabal install --bindir=./
clean:
rm -rf dist Setup.hs Code0809 *~

14
Ch08/Code09_dec/input.csv Normal file
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Sunny,Hot,High,Weak,No
Sunny,Hot,High,Strong,No
Overcast,Hot,High,Weak,Yes
Rain,Mild,High,Weak,Yes
Rain,Cool,Normal,Weak,Yes
Rain,Cool,Normal,Strong,No
Overcast,Cool,Normal,Strong,Yes
Sunny,Mild,High,Weak,No
Sunny,Cool,Normal,Weak,Yes
Rain,Mild,Normal,Weak,Yes
Sunny,Mild,Normal,Strong,Yes
Overcast,Mild,High,Strong,Yes
Overcast,Hot,Normal,Weak,Yes
Rain,Mild,High,Strong,No
1 Sunny Hot High Weak No
2 Sunny Hot High Strong No
3 Overcast Hot High Weak Yes
4 Rain Mild High Weak Yes
5 Rain Cool Normal Weak Yes
6 Rain Cool Normal Strong No
7 Overcast Cool Normal Strong Yes
8 Sunny Mild High Weak No
9 Sunny Cool Normal Weak Yes
10 Rain Mild Normal Weak Yes
11 Sunny Mild Normal Strong Yes
12 Overcast Mild High Strong Yes
13 Overcast Hot Normal Weak Yes
14 Rain Mild High Strong No

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-- Initial Code0810.cabal generated by cabal init. For further
-- documentation, see http://haskell.org/cabal/users-guide/
name: Code0810
version: 0.1.0.0
synopsis: Implementing k-Nearest Neighbors.
-- description:
homepage: haskelldata.com
license: GPL-2
license-file: ../LICENSE
author: Nishant Shukla
maintainer: nick722@gmail.com
-- copyright:
category: Classifying
build-type: Simple
-- extra-source-files:
cabal-version: >=1.10
executable Code0810
main-is: Main.hs
-- other-modules:
-- other-extensions:
build-depends: base >=4.6 && <4.7, KdTree >=0.2 && <0.3, iproute >=1.2 && <1.3, csv >=0.1 && <0.2, containers >=0.5 && <0.6
-- hs-source-dirs:
default-language: Haskell2010

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Ch08/Code10_knear/Main.hs Normal file
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import Data.Trees.KdTree
import Data.IP (IPv4, fromIPv4)
import Text.CSV
import qualified Data.Map as M
import Data.Maybe (fromJust)
ipToNum :: String -> Double
ipToNum str = fromIntegral $ sum $
zipWith (\a b -> a * 256^b) ns [0..]
where ns = reverse $ fromIPv4 (read str :: IPv4)
parse :: [Record] -> [(Point3d, String)]
parse [] = []
parse xs = map pair (cleanList xs)
where pair [ip, t, c] = (Point3d (ipToNum ip) (read t) 0.0, c)
cleanList = filter (\x -> length x == 3)
maxFreq :: [String] -> String
maxFreq xs = fst $ foldl myCompare ("", 0) freqs
where freqs = M.toList $ M.fromListWith (+) [(c, 1) | c <- xs]
myCompare (oldS, oldV) (s,v) = if v > oldV
then (s, v)
else (oldS, oldV)
test :: KdTree Point3d -> Int -> [(Point3d, String)] -> Point3d -> String
test kdtree k pairList p = maxFreq $ map classify neighbors
where neighbors = kNearestNeighbors kdtree k p
classify x = fromJust (lookup x pairList)
-- Running a k-nearest neighbor algorithm
main = do
rawCSV <- parseCSVFromFile "input.csv"
either handleError doWork rawCSV
handleError = error "Invalid CSV file"
doWork rawCSV = do
let ps = parse rawCSV
let kdtree = fromList (map fst ps)
let examples = [ ["71.190.100.100", "2000", "?"]
, ["216.239.33.1", "1", "?"] ]
let examplePts = map fst $ parse examples
print $ map (test kdtree 2 ps) examplePts

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default:
cabal install --bindir=./
clean:
rm -rf dist Setup.hs Code0810 *~

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71.190.189.171,8000,Human
71.191.90.170,9000,Human
71.191.91.1,8000,Human
216.239.32.0,5,Bot
216.239.32.10,10,Bot
216.239.32.5,5,Bot
1 71.190.189.171 8000 Human
2 71.191.90.170 9000 Human
3 71.191.91.1 8000 Human
4 216.239.32.0 5 Bot
5 216.239.32.10 10 Bot
6 216.239.32.5 5 Bot

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-- Initial Code0811.cabal generated by cabal init. For further
-- documentation, see http://haskell.org/cabal/users-guide/
name: Code0811
version: 0.1.0.0
synopsis: Plotting points.
-- description:
homepage: haskelldata.com
license: GPL-2
license-file: ../LICENSE
author: Nishant Shukla
maintainer: nick722@gmail.com
-- copyright:
category: Graphics
build-type: Simple
-- extra-source-files:
cabal-version: >=1.10
executable Code0811
main-is: Main.hs
-- other-modules:
-- other-extensions:
build-depends: base >=4.6 && <4.7, csv >=0.1 && <0.2, easyplot >=1.0 && <1.1
-- hs-source-dirs:
default-language: Haskell2010

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import Text.CSV
import Graphics.EasyPlot
tupes :: [[String]] -> [(Double, Double)]
tupes records = [(read x, read y) | [x, y] <- records]
-- Visualizing points
main = do
result <- parseCSVFromFile "input.csv"
case result of
Left err -> putStrLn "Error reading CSV file"
Right csv -> do
plot X11 $ Data2D [Title "Plot"] [] (tupes csv)
return ()

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default:
cabal install --bindir=./
clean:
rm -rf dist Setup.hs Code0811 plot1.dat *~

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1,2
2,3
3,1
4,5
5,3
6,1
1 1 2
2 2 3
3 3 1
4 4 5
5 5 3
6 6 1

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Ch08/LICENSE Normal file
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GNU GENERAL PUBLIC LICENSE
Version 2, June 1991
Copyright (C) 1989, 1991 Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
Preamble
The licenses for most software are designed to take away your
freedom to share and change it. By contrast, the GNU General Public
License is intended to guarantee your freedom to share and change free
software--to make sure the software is free for all its users. This
General Public License applies to most of the Free Software
Foundation's software and to any other program whose authors commit to
using it. (Some other Free Software Foundation software is covered by
the GNU Lesser General Public License instead.) You can apply it to
your programs, too.
When we speak of free software, we are referring to freedom, not
price. Our General Public Licenses are designed to make sure that you
have the freedom to distribute copies of free software (and charge for
this service if you wish), that you receive source code or can get it
if you want it, that you can change the software or use pieces of it
in new free programs; and that you know you can do these things.
To protect your rights, we need to make restrictions that forbid
anyone to deny you these rights or to ask you to surrender the rights.
These restrictions translate to certain responsibilities for you if you
distribute copies of the software, or if you modify it.
For example, if you distribute copies of such a program, whether
gratis or for a fee, you must give the recipients all the rights that
you have. You must make sure that they, too, receive or can get the
source code. And you must show them these terms so they know their
rights.
We protect your rights with two steps: (1) copyright the software, and
(2) offer you this license which gives you legal permission to copy,
distribute and/or modify the software.
Also, for each author's protection and ours, we want to make certain
that everyone understands that there is no warranty for this free
software. If the software is modified by someone else and passed on, we
want its recipients to know that what they have is not the original, so
that any problems introduced by others will not reflect on the original
authors' reputations.
Finally, any free program is threatened constantly by software
patents. We wish to avoid the danger that redistributors of a free
program will individually obtain patent licenses, in effect making the
program proprietary. To prevent this, we have made it clear that any
patent must be licensed for everyone's free use or not licensed at all.
The precise terms and conditions for copying, distribution and
modification follow.
GNU GENERAL PUBLIC LICENSE
TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
0. This License applies to any program or other work which contains
a notice placed by the copyright holder saying it may be distributed
under the terms of this General Public License. The "Program", below,
refers to any such program or work, and a "work based on the Program"
means either the Program or any derivative work under copyright law:
that is to say, a work containing the Program or a portion of it,
either verbatim or with modifications and/or translated into another
language. (Hereinafter, translation is included without limitation in
the term "modification".) Each licensee is addressed as "you".
Activities other than copying, distribution and modification are not
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running the Program is not restricted, and the output from the Program
is covered only if its contents constitute a work based on the
Program (independent of having been made by running the Program).
Whether that is true depends on what the Program does.
1. You may copy and distribute verbatim copies of the Program's
source code as you receive it, in any medium, provided that you
conspicuously and appropriately publish on each copy an appropriate
copyright notice and disclaimer of warranty; keep intact all the
notices that refer to this License and to the absence of any warranty;
and give any other recipients of the Program a copy of this License
along with the Program.
You may charge a fee for the physical act of transferring a copy, and
you may at your option offer warranty protection in exchange for a fee.
2. You may modify your copy or copies of the Program or any portion
of it, thus forming a work based on the Program, and copy and
distribute such modifications or work under the terms of Section 1
above, provided that you also meet all of these conditions:
a) You must cause the modified files to carry prominent notices
stating that you changed the files and the date of any change.
b) You must cause any work that you distribute or publish, that in
whole or in part contains or is derived from the Program or any
part thereof, to be licensed as a whole at no charge to all third
parties under the terms of this License.
c) If the modified program normally reads commands interactively
when run, you must cause it, when started running for such
interactive use in the most ordinary way, to print or display an
announcement including an appropriate copyright notice and a
notice that there is no warranty (or else, saying that you provide
a warranty) and that users may redistribute the program under
these conditions, and telling the user how to view a copy of this
License. (Exception: if the Program itself is interactive but
does not normally print such an announcement, your work based on
the Program is not required to print an announcement.)
These requirements apply to the modified work as a whole. If
identifiable sections of that work are not derived from the Program,
and can be reasonably considered independent and separate works in
themselves, then this License, and its terms, do not apply to those
sections when you distribute them as separate works. But when you
distribute the same sections as part of a whole which is a work based
on the Program, the distribution of the whole must be on the terms of
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entire whole, and thus to each and every part regardless of who wrote it.
Thus, it is not the intent of this section to claim rights or contest
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exercise the right to control the distribution of derivative or
collective works based on the Program.
In addition, mere aggregation of another work not based on the Program
with the Program (or with a work based on the Program) on a volume of
a storage or distribution medium does not bring the other work under
the scope of this License.
3. You may copy and distribute the Program (or a work based on it,
under Section 2) in object code or executable form under the terms of
Sections 1 and 2 above provided that you also do one of the following:
a) Accompany it with the complete corresponding machine-readable
source code, which must be distributed under the terms of Sections
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years, to give any third party, for a charge no more than your
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distributed under the terms of Sections 1 and 2 above on a medium
customarily used for software interchange; or,
c) Accompany it with the information you received as to the offer
to distribute corresponding source code. (This alternative is
allowed only for noncommercial distribution and only if you
received the program in object code or executable form with such
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The source code for a work means the preferred form of the work for
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4. You may not copy, modify, sublicense, or distribute the Program
except as expressly provided under this License. Any attempt
otherwise to copy, modify, sublicense or distribute the Program is
void, and will automatically terminate your rights under this License.
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may not distribute the Program at all. For example, if a patent
license would not permit royalty-free redistribution of the Program by
all those who receive copies directly or indirectly through you, then
the only way you could satisfy both it and this License would be to
refrain entirely from distribution of the Program.
If any portion of this section is held invalid or unenforceable under
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It is not the purpose of this section to induce you to infringe any
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implemented by public license practices. Many people have made
generous contributions to the wide range of software distributed
through that system in reliance on consistent application of that
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to distribute software through any other system and a licensee cannot
impose that choice.
This section is intended to make thoroughly clear what is believed to
be a consequence of the rest of this License.
8. If the distribution and/or use of the Program is restricted in
certain countries either by patents or by copyrighted interfaces, the
original copyright holder who places the Program under this License
may add an explicit geographical distribution limitation excluding
those countries, so that distribution is permitted only in or among
countries not thus excluded. In such case, this License incorporates
the limitation as if written in the body of this License.
9. The Free Software Foundation may publish revised and/or new versions
of the General Public License from time to time. Such new versions will
be similar in spirit to the present version, but may differ in detail to
address new problems or concerns.
Each version is given a distinguishing version number. If the Program
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either of that version or of any later version published by the Free
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Foundation.
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NO WARRANTY
11. BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY
FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN
OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES
PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED
OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS
TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE
PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING,
REPAIR OR CORRECTION.
12. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR
REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES,
INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING
OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED
TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY
YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER
PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
POSSIBILITY OF SUCH DAMAGES.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
convey the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
Also add information on how to contact you by electronic and paper mail.
If the program is interactive, make it output a short notice like this
when it starts in an interactive mode:
Gnomovision version 69, Copyright (C) year name of author
Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, the commands you use may
be called something other than `show w' and `show c'; they could even be
mouse-clicks or menu items--whatever suits your program.
You should also get your employer (if you work as a programmer) or your
school, if any, to sign a "copyright disclaimer" for the program, if
necessary. Here is a sample; alter the names:
Yoyodyne, Inc., hereby disclaims all copyright interest in the program
`Gnomovision' (which makes passes at compilers) written by James Hacker.
<signature of Ty Coon>, 1 April 1989
Ty Coon, President of Vice
This General Public License does not permit incorporating your program into
proprietary programs. If your program is a subroutine library, you may
consider it more useful to permit linking proprietary applications with the
library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License.

View File

@ -6,8 +6,20 @@ Refer to the book for step-by-step explanations.
<p align="center"><a href="http://haskelldata.com" target="_blank"><img src="http://haskelldata.com/images/ch08.png"/></a></p>
# How to use
# Recipes:
* **Code01**: Implementing the k-means clustering algorithm
* **Code02**: Implementing hierarchical clustering
* **Code03**: Using a hierarchical clustering library
* **Code04**: Finding the number of clusters
* **Code05**: Clustering words by their lexemes
* **Code06**: Classifying the parts of speech of words
* **Code07**: Identifying key words in a corpus of text
* **Code08**: Training a parts of speech tagger
* **Code09**: Implementing a decision tree classifier
* **Code10**: Implementing a k-Nearest Neighbors classifier
* **Code11**: Visualizing points using Graphics.EasyPlot
# How to use
### Setting up the environment
Install the [Haskell Platform](http://www.haskell.org/platform/).