Merge pull request #280 from fch-aa/Fix-SMO-CacheSize

Fixes SMO's CacheSize being overridden
accord-net · Aug 25, 2016 · e98bb92 · e98bb92
2 parents d041d80 + b6e306b
commit e98bb92
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Showing 2 changed files with 63 additions and 3 deletions.
diff --git a/Sources/Accord.MachineLearning/VectorMachines/Learning/SequentialMinimalOptimization.cs b/Sources/Accord.MachineLearning/VectorMachines/Learning/SequentialMinimalOptimization.cs
@@ -402,7 +402,7 @@ public abstract class BaseSequentialMinimalOptimization<TModel, TKernel, TInput>
         // Error cache to speed up computations
         private double[] errors;
 
-        private int cacheSize;
+        private int cacheSize = -1;
         private KernelFunctionCache<TKernel, TInput> kernelCache;
 
         private SelectionStrategy strategy = SelectionStrategy.WorstPair;
@@ -478,7 +478,7 @@ public int CacheSize
             get { return cacheSize; }
             set
             {
-                if (cacheSize < 0)
+                if (value < 0)
                     throw new ArgumentOutOfRangeException("value");
                 this.cacheSize = value;
             }
@@ -575,7 +575,10 @@ protected override void InnerRun()
             this.errors = new double[samples];
 
             // Kernel cache
-            this.cacheSize = samples;
+            if (this.cacheSize == -1)
+            {
+                this.cacheSize = samples;
+            }
 
 
             // Lagrange multipliers

diff --git a/Unit Tests/Accord.Tests.MachineLearning/VectorMachines/SequentialMinimalOptimizationTest.cs b/Unit Tests/Accord.Tests.MachineLearning/VectorMachines/SequentialMinimalOptimizationTest.cs
@@ -421,6 +421,63 @@ public void LearnTest5()
             }
         }
 
+        [Test]
+        public void Learn_UnspecifiedCacheSize_CacheSizeEqualsInputLength()
+        {
+            double[][] inputs =
+            {
+                new double[] { -1, -1 },
+                new double[] { -1,  1 },
+                new double[] {  1, -1 },
+                new double[] {  1,  1 }
+            };
+
+            int[] xor =
+            {
+                -1,
+                 1,
+                 1,
+                -1
+            };
+
+            KernelSupportVectorMachine svm = new KernelSupportVectorMachine(new Polynomial(2), inputs[0].Length);
+            SequentialMinimalOptimization smo = new SequentialMinimalOptimization(svm, inputs, xor);
+
+            smo.Run();
+
+            Assert.AreEqual(smo.CacheSize, inputs.Length);
+        }
+
+        [Test]
+        public void Learn_CacheSizeZero_CacheSizeShouldBeZero()
+        {
+            double[][] inputs =
+            {
+                new double[] { -1, -1 },
+                new double[] { -1,  1 },
+                new double[] {  1, -1 },
+                new double[] {  1,  1 }
+            };
+
+            int[] xor =
+            {
+                -1,
+                 1,
+                 1,
+                -1
+            };
+
+            KernelSupportVectorMachine svm = new KernelSupportVectorMachine(new Polynomial(2), inputs[0].Length);
+            SequentialMinimalOptimization smo = new SequentialMinimalOptimization(svm, inputs, xor)
+            {
+                CacheSize = 0
+            };
+
+            smo.Run();
+
+            Assert.AreEqual(smo.CacheSize, 0);
+        }
+
         [Test]
         public void LargeLearningTest1()
         {