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//こちらのプログラムを移植してみた。解説も詳しくて勉強になる。
//http://d.hatena.ne.jp/aidiary/20100613/1276389337
object NaiveBayes {
  type Category = String
  type Word = String

  case class Data(category: Category, words: List[Word])

  def train(data: List[Data]) = new NBClassifier(data)

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//HANSEIとはprobabilistic programmingを行うためのtaglessなインタプリタのこと。
//確率モデルをプログラムの形で書くとパラメータの推論を自動で行なってくれる。
//oleg氏の論文だとreify/reflectを使ったdirect styleのモナドで記述されている。
//http://okmij.org/ftp/kakuritu

//要はこちらのスライドで紹介されているものをmonadやHOASを使って内部DSLとして実装したもの。
//http://www.slideshare.net/tsubosaka/infernetlda

//こちらの方の記事も参考になる。
//http://d.hatena.ne.jp/rst76/20100706/1278430517

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(* 何かがおかしい。要検証。 *)
module MCMC =
  let random = new Random()
  let select x = x + (random.NextDouble() - 0.5) * 10.0
  
  let prob x = 1.0 / (1.0 + System.Math.Exp(-x))

  let nextStatus x = 
    let xt = select x
    let p = prob xt / prob x

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open System

type Class = Virus | Noise
type Datum = { Image : float[]; Class : Class }

type NeuralNetwork(inputSize, hiddenSize, outputSize, patternSize, maxT, eps, alpha, beta, W0, high, low) =
    let mutable eta = 0.005

    let inputLayer = Array.init (inputSize+1) (fun _ -> 0.0)
    let hiddenLayer = Array.init (hiddenSize+1) (fun _ -> 0.0)

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type Tree<'T when 'T : comparison> = Null | Fork of 'T * Tree<'T> * Tree<'T>

let isEmpty = function
  | Null -> true
  | _ -> false

let minElem (Fork(x,_,_)) = x

let rec merge a b =

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let levenshteinDistance (str1 : string) (str2 : string) =
   let d = Array.init (str1.Length+1) (fun _ -> Array.init (str2.Length+1) (fun _ -> 0))
   let mutable cost = 0 
   for i1 = 0 to str1.Length do
       d.[i1].[0] <- i1
   for i2 = 0 to str2.Length do
       d.[0].[i2] <- i2
   for i1 = 1 to str1.Length do
       for i2 = 1 to str2.Length do
           if str1.[i1-1] = str2.[i2-1] then

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type ty =
 | TyVar of int * int
 | TyArr of ty * ty
 | TyAll of string * ty
 | TySome of string * ty

type binding =
 | NameBind
 | VarBind of ty
 | TyVarBind

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let [| n; sum |] = System.Console.ReadLine().Split([|' '|]) |> Array.map int

let rec permutations list taken = 
  seq { if Set.count taken = List.length list then yield [] else
        for l in list do
          if not (Set.contains l taken) then 
            for perm in permutations list (Set.add l taken)  do
              yield l::perm }

let step xs = seq {

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let size = System.Console.ReadLine() |> int
let input = [|
  for i = 0 to size - 1 do
    yield System.Console.ReadLine().Split([|' '|]) |> Array.map int
|]

let rec permutations list taken = 
  seq { if Set.count taken = List.length list then yield [] else
        for l in list do
          if not (Set.contains l taken) then 

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module Util =
  let toStr x = Array.fold (fun x y -> x + string y) "" x
  let fordir (arr : int[]) x f =
    for (i, d) in List.mapi (fun a b -> (a, b)) [ 1; -1; 4; -4 ] do
      if not(x%4=0 && i=1) && not(x%4=3 && i=0) && x+d<8 && x+d>=0 then
        let arr = arr.Clone() :?> int[]
        let t = arr.[x]
        arr.[x] <- arr.[x + d]
        arr.[x + d] <- t
        f arr