Refactor and add Cluster Model.

src/ML.Core.Test/ModelTest.cs

@@ -7,6 +7,7 @@
 using ML.Core.Data.Loader;
 using ML.Core.Metrics;
 using ML.Core.Metrics.Categorical;
+using ML.Core.Metrics.Regression;
 using ML.Core.Models;
 using ML.Core.Optimizers;
 using ML.Core.Trainers;
@@ -183,33 +184,16 @@ private Dataset<DataView> GetIris<T>(string path) where T : DataView
         public void TestKNN()
         {
             var trainDataset = GetIris<IrisData>("iris-train.txt").ToDatasetNDarray();
-            var knn = new KNN(5);
+            var knn = new KNN(2);
             knn.LoadDataView(trainDataset.Feature, trainDataset.Label);
 
-            var x = trainDataset.Feature;
-            var y = trainDataset.Label;
 
-            var input = new Dataset<IrisData>(new[]
-            {
-                new IrisData
-                {
-                    SepalLength = 6.6,
-                    SepalWidth = 2.9,
-                    PetalLength = 4.6,
-                    PetalWidth = 1.3
-                },
-                new IrisData
-                {
-                    SepalLength = 7.2,
-                    SepalWidth = 3.5,
-                    PetalLength = 6.1,
-                    PetalWidth = 2.4
-                }
-            }).ToDatasetNDarray().Feature;
-
-
-            var res = knn.Call(input);
-            print(res);
+            var testDataset = GetIris<IrisData>("iris-test.txt").ToDatasetNDarray();
+            var Y_pred = knn.Call(testDataset.Feature);
+            print(Y_pred);
+            print(testDataset.Label);
+            var categoricalAcc = new MeanSquaredError().Call(testDataset.Label, Y_pred);
+            print(categoricalAcc);
         }
     }
 }

src/ML.Core/ML.Core.csproj

@@ -181,14 +181,16 @@
     <Compile Include="Metrics\Regression\MeanSquaredError.cs" />
     <Compile Include="Metrics\Regression\MeanSquaredLogarithmicError.cs" />
     <Compile Include="Metrics\Regression\RSquared.cs" />
-    <Compile Include="Models\BinaryLogicClassify.cs" />
+    <Compile Include="Models\Cluster\Cluster.cs" />
+    <Compile Include="Models\Cluster\KMeans.cs" />
+    <Compile Include="Models\Supervised\BinaryLogicClassify.cs" />
     <Compile Include="Models\Interface\IModel.cs" />
     <Compile Include="Models\Interface\IModelGD.cs" />
     <Compile Include="Models\KNN.cs" />
-    <Compile Include="Models\ModelGD.cs" />
-    <Compile Include="Models\MultipleLinearRegression.cs" />
-    <Compile Include="Models\Perceptron.cs" />
-    <Compile Include="Models\PolynomialRegression.cs" />
+    <Compile Include="Models\Supervised\ModelGD.cs" />
+    <Compile Include="Models\Supervised\MultipleLinearRegression.cs" />
+    <Compile Include="Models\Supervised\Perceptron.cs" />
+    <Compile Include="Models\Supervised\PolynomialRegression.cs" />
     <Compile Include="Optimizers\AdaDelta.cs" />
     <Compile Include="Optimizers\AdaGrad.cs" />
     <Compile Include="Optimizers\Adam.cs" />

src/ML.Core/ML.Core.csproj.DotSettings

@@ -2,6 +2,8 @@
 	<s:Boolean x:Key="/Default/CodeInspection/NamespaceProvider/NamespaceFoldersToSkip/=losses_005Cbinarylosses/@EntryIndexedValue">True</s:Boolean>
 	<s:Boolean x:Key="/Default/CodeInspection/NamespaceProvider/NamespaceFoldersToSkip/=losses_005Ccategoricallosses/@EntryIndexedValue">True</s:Boolean>
 	<s:Boolean x:Key="/Default/CodeInspection/NamespaceProvider/NamespaceFoldersToSkip/=losses_005Cregressionlosses/@EntryIndexedValue">True</s:Boolean>
+	<s:Boolean x:Key="/Default/CodeInspection/NamespaceProvider/NamespaceFoldersToSkip/=models_005Ccluster/@EntryIndexedValue">True</s:Boolean>
 	<s:Boolean x:Key="/Default/CodeInspection/NamespaceProvider/NamespaceFoldersToSkip/=models_005Cinterface/@EntryIndexedValue">True</s:Boolean>
+	<s:Boolean x:Key="/Default/CodeInspection/NamespaceProvider/NamespaceFoldersToSkip/=models_005Csupervised/@EntryIndexedValue">True</s:Boolean>
 	<s:Boolean x:Key="/Default/CodeInspection/NamespaceProvider/NamespaceFoldersToSkip/=optimizers_005Cannealings/@EntryIndexedValue">True</s:Boolean>
 	<s:Boolean x:Key="/Default/CodeInspection/NamespaceProvider/NamespaceFoldersToSkip/=optimizer_005Cannealings/@EntryIndexedValue">True</s:Boolean></wpf:ResourceDictionary>

src/ML.Core/Models/Cluster/Cluster.cs

@@ -0,0 +1,27 @@
+using GalaSoft.MvvmLight;
+using Numpy;
+
+namespace ML.Core.Models
+{
+    public abstract class Cluster : ViewModelBase
+    {
+        private int _k;
+
+        /// <summary>
+        ///     聚类算法抽象类
+        /// </summary>
+        /// <param name="k"></param>
+        protected Cluster(int k)
+        {
+            K = k;
+        }
+
+        public int K
+        {
+            get => _k;
+            set => Set(ref _k, value);
+        }
+
+        public abstract NDarray Call(NDarray input);
+    }
+}

src/ML.Core/Models/Cluster/KMeans.cs

@@ -0,0 +1,17 @@
+using System;
+using Numpy;
+
+namespace ML.Core.Models
+{
+    public class KMeans : Cluster
+    {
+        public KMeans(int k) : base(k)
+        {
+        }
+
+        public override NDarray Call(NDarray input)
+        {
+            throw new NotImplementedException();
+        }
+    }
+}

src/ML.Core/Models/KNN.cs

@@ -1,5 +1,4 @@
-using System;
-using System.Collections.Generic;
+using System.Collections.Generic;
 using System.Linq;
 using FluentAssertions;
 using ML.Core.Data;
@@ -21,13 +20,13 @@ public KNN(int k, bool regression = false)
         public NDarray Features { get; set; }
 
         public NDarray Labels { get; set; }
+        public string Name => GetType().Name;
         public NDarray Weights { get; set; }
-
-        public string WeightFile { get; }
+        public string WeightFile => $"{Name}.txt";
 
         public double[] GetWeightArray()
         {
-            throw new NotImplementedException();
+            return null;
         }