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Algorithm F#程序未运行到完成_Algorithm_F#_K Means - Fatal编程技术网

Algorithm F#程序未运行到完成

Algorithm F#程序未运行到完成,algorithm,f#,k-means,Algorithm,F#,K Means,我试图执行一个F#脚本,它是作为fs程序而不是脚本复制的。我已经下载了我正在使用的所有库,并在其他环境中对它们进行了测试,它们都可以工作。它可以正确编译csv文件并将其排序到数组中,但在以下情况下不会执行: let labels = fileAsLines |> Array.map (fun line -> line.[4]) dataset, labels 提前感谢您的帮助,我一直在阅读和使用这个论坛频繁,并感谢所有的指导 // Learn more about F# at ht

我试图执行一个F#脚本,它是作为fs程序而不是脚本复制的。我已经下载了我正在使用的所有库,并在其他环境中对它们进行了测试,它们都可以工作。它可以正确编译csv文件并将其排序到数组中,但在以下情况下不会执行:

let labels = fileAsLines |> Array.map (fun line -> line.[4])
dataset, labels
提前感谢您的帮助,我一直在阅读和使用这个论坛频繁,并感谢所有的指导

// Learn more about F# at http://fsharp.net
// Code from http://www.clear-lines.com/blog/post/Nearest-Neighbor-Classification-part-2.aspx

open MicrosoftResearch.Infer.Fun.FSharp.Syntax
open MicrosoftResearch.Infer.Fun.FSharp.Inference
open MicrosoftResearch.Infer.Fun.Lib
open MicrosoftResearch.Infer.Maths
open System.IO
open System
open System.Drawing
open MSDN.FSharp.Charting

let distance v1 v2 =
    Array.zip v1 v2
    |> Array.fold (fun sum e -> sum + pown (fst e - snd e) 2) 0.0|> sqrt

let classify subject dataset labels k =
    dataset
    |> Array.map (fun row -> distance row subject)
    |> Array.zip labels
    |> Array.sortBy snd
    |> Array.toSeq
    |> Seq.take k
    |> Seq.groupBy fst
    |> Seq.maxBy (fun g -> Seq.length (snd g))
let column (dataset: float [][]) i =
        dataset |> Array.map (fun row -> row.[i])

let columns (dataset: float [][]) =
    let cols = dataset.[0] |> Array.length
    [| for i in 0 .. (cols - 1) -> column dataset i |]

let minMax dataset =
    dataset
    |> columns
    |> Array.map (fun col -> Array.min(col), Array.max(col))

let minMaxNormalizer dataset =
    let bounds = minMax dataset
    fun (vector: float[]) ->
        Array.mapi (fun i v ->
            (vector.[i] - fst v) / (snd v - fst v)) bounds

let normalize data (normalizer: float[] -> float[]) =
    data |> Array.map normalizer

let classifier dataset labels k =
    let normalizer = minMaxNormalizer dataset
    let normalized = normalize dataset normalizer
    fun subject -> classify (normalizer(subject)) normalized labels k

let elections =
    let file = @"C:\Users\Jessica\Dataset\Election2008.txt"
    let fileAsLines =
        File.ReadAllLines(file)
            |> Array.map (fun line -> line.Split(','))
    let dataset =
        fileAsLines
        |> Array.map (fun line ->
            [| Convert.ToDouble(line.[1]);
               Convert.ToDouble(line.[2]);
               Convert.ToDouble(line.[3]) |])
    let labels = fileAsLines |> Array.map (fun line -> line.[4])
    dataset, labels

let evaluate dataset (labels: string []) k prop =
    let size = dataset |> Array.length
    let sample = floor ((float)size * prop) |> (int)
    let testSubjects, testLabels = dataset.[0 .. sample-1], labels.[0..sample-1]
    let trainData = dataset.[sample .. size-1], labels.[sample .. size-1]
    let c = classifier (fst trainData) (snd trainData) k   
    let results =
        testSubjects
        |> Array.mapi (fun i e -> fst (c e), testLabels.[i])
    results
    |> Array.iter (fun e -> printfn "%s %s" (fst e) (snd e))
    let correct =
       results
        |> Array.filter (fun e -> fst e = snd e)
        |> Array.length
    printfn "%i out of %i called correctly" correct sample

执行
let elections
块中的代码的原因是它被定义为一个值而不是一个函数(它不接受任何参数,也不接受单位
()
)。这意味着它是在声明时执行的

脚本中紧随其后的唯一代码声明了一个函数(称为
evaluate
;它看起来很相似,但它带有参数,因此除非有东西调用它并提供所需的参数,否则不会执行),但您没有任何调用它的代码

我认为最简单的改变是:

  • 从函数
    evaluate
    末尾删除
    k
    prop
    参数(这些参数似乎未被使用)
  • 在脚本的最后,使用存储在
    elections
    中的值调用
    evaluate
    方法,如下所示:

    let数据集,labels=elections

    评估数据集标签

  • 稍微重新构造代码可能是有意义的,因为在
    选举
    声明期间执行代码似乎有点令人困惑,但一旦代码正常工作,重新构造和理解所发生的事情可能会更容易