ExtremeLearning

README.md

@@ -38,6 +38,8 @@ A very light weight Scala machine learning library that provide some basic ML al
 
 - [x] Random Forest [[Code]](src/main/scala/algorithm/classification/RandomForest.scala) [[Usage]](src/test/scala/algorithm/classification/RandomForestTest.scala)
 
+- [x] Extreme Learning Machine [[Code]](src/main/scala/algorithm/classification/ExtremeLearning.scala) [[Usage]](src/test/scala/algorithm/classification/ExtremeLearningTest.scala)
+
 ### Boost :
 
 - [x] Naive Boost [[Code]](src/main/scala/algorithm/classification/NaiveBoost.scala) [[Usage]](src/test/scala/algorithm/classification/NaiveBoostTest.scala)
@@ -123,8 +125,6 @@ A very light weight Scala machine learning library that provide some basic ML al
 
 ## TODO
 
-- [ ] Extreme Learning Machine - Classification
-
 - [ ] Polarize Experience Replay - Deep Reinforcement Learning
 
 - [ ] Rainbow - Deep Reinforcement Learning

src/main/scala/algorithm/classification/ExtremeLearning.scala

@@ -0,0 +1,31 @@
+// Wei Chen - Extreme Learning
+// 2020-03-08
+
+package com.scalaml.algorithm
+import com.scalaml.general.MatrixFunc._
+
+class ExtremeLearning(val neuronNumber: Int, val featureNumber: Int, val outputNumber: Int) {
+    var wIn = matrixrandom(featureNumber, neuronNumber, -1, 1)
+    var wOut = matrixrandom(neuronNumber, outputNumber, -1, 1)
+
+    def clear() = {
+        wIn = matrixrandom(featureNumber, neuronNumber, -1, 1)
+        wOut = matrixrandom(neuronNumber, outputNumber, -1, 1)
+    }
+    clear()
+
+    private def reluLayer(x: Array[Array[Double]]): Array[Array[Double]] = {
+        matrixdot(x, wIn).map(arr => arr.map(v => math.max(0, v)))
+    }
+
+    def train(x: Array[Array[Double]], y: Array[Array[Double]]) {
+        val outX = reluLayer(x)
+        val tranX = outX.transpose
+        wOut = matrixdot(inverse(matrixdot(tranX, outX)), matrixdot(tranX, y))
+    }
+
+    def predict(x: Array[Array[Double]]): Array[Array[Double]] = {
+        val outX = reluLayer(x)
+        matrixdot(outX, wOut)
+    }
+}

src/test/scala/algorithm/classification/ExtremeLearningTest.scala

@@ -0,0 +1,33 @@
+// Wei Chen - Extreme Learning Test
+// 2016-11-06
+
+import com.scalaml.TestData._
+import com.scalaml.general.MatrixFunc._
+import com.scalaml.algorithm.ExtremeLearning
+import org.scalatest.funsuite.AnyFunSuite
+
+class ExtremeLearningSuite extends AnyFunSuite {
+
+    val neuronNumber = 100
+    val featureNumber = UNLABELED_LARGE_HIGH_DIM_DATA.head.size
+    val outputNumber = TARGET_LARGE_HIGH_DIM_DATA.head.size
+
+    val el = new ExtremeLearning(neuronNumber, featureNumber, outputNumber)
+    test("ExtremeLearning Test : Initialization") {
+        assert(el.wIn.size == featureNumber)
+        assert(el.wIn.head.size == neuronNumber)
+        assert(el.wOut.size == neuronNumber)
+        assert(el.wOut.head.size == outputNumber)
+    }
+
+    test("ExtremeLearning Test : Train") {
+        el.train(UNLABELED_LARGE_HIGH_DIM_DATA, TARGET_LARGE_HIGH_DIM_DATA)
+        val result = el.predict(UNLABELED_LARGE_HIGH_DIM_DATA)
+        assert(matrixsimilar(result, TARGET_LARGE_HIGH_DIM_DATA, 0.5))
+    }
+
+    test("ExtremeLearning Test : Predict - OVERFITS LIKE CRAZY W/O ENOUGH DATA") {
+        val result = el.predict(UNLABELED_SMALL_HIGH_DIM_DATA)
+        assert(matrixsimilar(result, TARGET_SMALL_HIGH_DIM_DATA, neuronNumber))
+    }
+}