using System;

using Accord.Statistics.Models.Markov;

using Accord.Statistics.Models.Markov.Learning;

using Accord.Statistics.Models.Markov.Topology;

using Serilog;

using System.Collections.Generic;

using System.Linq;

public class Program

{

    enum Tags { 家電愛好者, 愛漂亮的人};

    static string [] objs = { "耳機", "行動電源","掃地機", "面膜", "防曬乳","保濕乳", "未知"};

    //監督式的機器學習

    //本機器學習範例，透過七組使用者的序列資料，及label，進行訓練

    //最後再餵入任意二個序列，預測他是哪一種label

    public static void Main()

    {

        Log.Logger = new LoggerConfiguration()

        .WriteTo.Console()

        .CreateLogger();

        //物件標簽

        //訓練輸入，使用者最近幾次的流覽物件

        string [][] inputs = new string [][]

        {

            new string[] { "耳機","行動電源","行動電源", "行動電源", "耳機"},   

            new string[] { "耳機","耳機","行動電源", "行動電源", "耳機", "耳機"},  

            new string[] { "耳機","行動電源","行動電源", "行動電源",  "行動電源", "耳機"},   

            new string[] { "面膜","面膜","面膜","面膜", "保濕乳"},   

            new string[] { "面膜", "面膜","保濕乳","面膜","面膜","面膜"},   

            new string[] { "面膜", "面膜","保濕乳","面膜","面膜","面膜"},  

            new string[] { "面膜", "保濕乳","面膜","面膜","面膜","面膜"},   

        };

        //訓練輸入，給使用者定義類型

        int [] inputlabel = new int[]       

        {

            Tags.家電愛好者.ToInt32(),

            Tags.家電愛好者.ToInt32(),

            Tags.家電愛好者.ToInt32(),

            Tags.愛漂亮的人.ToInt32(),

            Tags.愛漂亮的人.ToInt32(),

            Tags.愛漂亮的人.ToInt32(),

            Tags.愛漂亮的人.ToInt32()

        };

        ITopology forward = new Forward(states: 3);

        HiddenMarkovClassifier classifier = new HiddenMarkovClassifier(classes: 2,  topology: forward, symbols: objs.Count());

        //建立一個新的學習演算法來訊練序列分類器

        var teacher = new HiddenMarkovClassifierLearning(classifier,// Train each model until the log-likelihood changes less than 0.001

            modelIndex => new BaumWelchLearning(classifier.Models[modelIndex]) {

            Tolerance = 0.001,

            Iterations = 0

        });

        //開始訓練模型

        double likelihood = teacher.Run(inputs.ToCode(objs), inputlabel);

        //=============================================

        //開始預測使用者1，輸入最近六次的路徑

        int user1 = classifier.Compute( (new[] { "行動電源","掃地機" ,"耳機", "防曬乳" ,"面膜", "耳機"}).ToCode(objs));         

        Log.Information("第一位使用者是:{user1}", (Tags)user1);

        //開始預測使用者2，輸入最近六次的路徑

        int user2 = classifier.Compute( (new[] {"面膜","保濕乳" ,"面膜","面膜","面膜", "保濕乳" ,"面膜"}).ToCode(objs)); 

        Log.Information("第二位使用者是:{user2}", (Tags)user2);

    }   

​

}

​

​

public static class Helper

{

    public static int[][] ToCode(this string [][] input, string[] tags)

    {

        return input.Select(arr => arr.Select( obj => tags.IndexOf(obj) ).ToArray() ).ToArray();

    }

    public static int[] ToCode(this string [] input, string[] tags)

    {

        return input.Select( obj => tags.IndexOf(obj) ).ToArray();

    }

}