Added more elemental matrix math and a non functioning gradient decent function.

src/zutil/math/Matrix.java

@@ -146,6 +146,42 @@ public class Matrix {
             return result;
         }
 
+        /**
+         * Matrix Vector elemental multiplication, each element column in the matrix will be
+         * multiplied with the column  of the vector.
+         *
+         * @return a new matrix with the result
+         */
+        public static double[][] multiply(double[][] matrix, double[] vector){
+            vectorPreCheck(matrix, vector);
+            double[][] result = new double[matrix.length][matrix[0].length];
+
+            for (int y=0; y < matrix.length; ++y) {
+                for (int x=0; x<matrix[0].length; ++x) {
+                    result[y][x] = matrix[y][x] * vector[x];
+                }
+            }
+            return result;
+        }
+
+        /**
+         * Matrix Vector elemental division, each element column in the matrix will be
+         * divided with the column of the vector.
+         *
+         * @return a new matrix with the result
+         */
+        public static double[][] divide(double[][] matrix, double[] vector){
+            vectorPreCheck(matrix, vector);
+            double[][] result = new double[matrix.length][matrix[0].length];
+
+            for (int y=0; y < matrix.length; ++y) {
+                for (int x=0; x<matrix[0].length; ++x) {
+                    result[y][x] = matrix[y][x] / vector[x];
+                }
+            }
+            return result;
+        }
+
         /**
          * Element exponential, each element in the vector will raised
          * to the power of the exp paramter
@@ -181,7 +217,7 @@ public class Matrix {
             if (matrix1.length != matrix2.length || matrix1[0].length != matrix2[0].length)
                 throw new IllegalArgumentException("Matrices need to be of same dimension: " +
                         "matrix1 " + matrix1.length + "x" + matrix1[0].length + ", " +
-                        "matrix2 " + matrix2.length + "x" + matrix2[0].length + ", ");
+                        "matrix2 " + matrix2.length + "x" + matrix2[0].length);
         }
     }
 
@@ -374,7 +410,7 @@ public class Matrix {
         if (matrix1[0].length != matrix2.length)
             throw new IllegalArgumentException("Matrix1 columns need to match Matrix2 rows: " +
                     "matrix1 " + matrix1.length + "x" + matrix1[0].length + ", " +
-                    "matrix2 " + matrix2.length + "x" + matrix2[0].length + ", ");
+                    "matrix2 " + matrix2.length + "x" + matrix2[0].length);
     }
 
     /***********************************************************************

src/zutil/ml/LinearRegression.java

@@ -1,13 +1,16 @@
 package zutil.ml;
 
+import zutil.log.LogUtil;
 import zutil.math.Matrix;
 
+import java.util.logging.Logger;
+
 /**
- * Implementation of a Linear Regression algorithm for "predicting"
+ * Implementation of a Linear Regression algorithm for predicting
  * numerical values depending on specific input
  */
 public class LinearRegression {
-
+    private static final Logger logger = LogUtil.getLogger();
 
     /**
      * Method for calculating a hypothesis value fr a specific input value x.
@@ -37,6 +40,34 @@ public class LinearRegression {
                 Matrix.Elemental.pow(normalized,2));
     }
 
+    /**
+     * Calculates the gradiant of the current provided theta.
+     */
+    protected static double calculateGradiant(double[][] x, double[] y, double[] theta){
+        int m = y.length; // number of training examples
+        double[] hypothesis = calculateHypothesis(x, theta);
+        double[] normalized = Matrix.subtract(hypothesis, y);
+
+        return 1/m * Matrix.sum(
+                Matrix.Elemental.multiply(Matrix.transpose(x), normalized));
+
+    }
+
+    /**
+     * Will try to find the best theta value.
+     */
+    public static double[] gradientDescent(double[][] x, double[] y, double[] theta, double alpha){
+        double[] newTheta = theta.clone();
+        double gradient;
+
+        for (int i=0; (gradient = calculateGradiant(x, y, newTheta)) != 0; i++) {
+            logger.fine("Gradient Descent iteration " + i + ", gradiant: " + gradient);
+            newTheta = gradientDescentIteration(x, y, newTheta, alpha);
+        }
+
+        return newTheta;
+    }
+
     /**
      * Gradient Descent algorithm
      * <br /><br />