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Implemented Gradient Ascent (TCs failing)

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This commit is contained in:
Ziver Koc 2018-04-17 17:03:34 +02:00
parent 8050170ee3
commit 2160976406
4 changed files with 187 additions and 15 deletions
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47
test/zutil/math/MatrixTest.java
View file

@ -70,14 +70,46 @@ public class MatrixTest {
@Test
public void vectorMultiply(){
public void vectorAddition(){
assertArrayEquals(
new double[]{8,14},
Matrix.multiply(new double[][]{{2,3},{-4,9}}, new double[]{1,2}),
new double[]{3,5,-1,13},
Matrix.add(new double[]{2,3,-4,9}, new double[]{1,2,3,4}),
0.0
);
}
@Test
public void vectorMatrixAddition(){
assertArrayEquals(
new double[][]{{2,3,4,5},{2,3,4,5},{2,3,4,5},{2,3,4,5}},
Matrix.add(new double[][]{{1,2,3,4},{1,2,3,4},{1,2,3,4},{1,2,3,4}}, new double[]{1,1,1,1})
);
}
@Test
public void vectorSubtraction(){
assertArrayEquals(
new double[]{1,1,-7,5},
Matrix.subtract(new double[]{2,3,-4,9}, new double[]{1,2,3,4}),
0.0
);
}
@Test
public void vectorMatrixSubtraction(){
assertArrayEquals(
new double[][]{{0,1,2,3},{0,1,2,3},{0,1,2,3},{0,1,2,3}},
Matrix.subtract(new double[][]{{1,2,3,4},{1,2,3,4},{1,2,3,4},{1,2,3,4}}, new double[]{1,1,1,1})
);
}
@Test
public void vectorMultiply(){
assertArrayEquals(
new double[][]{{8},{14}},
Matrix.multiply(new double[][]{{2,3},{-4,9}}, new double[]{1,2}));
}
@Test
public void vectorDivision(){
assertArrayEquals(
@ -138,4 +170,13 @@ public class MatrixTest {
new double[][]{{1,0,0,0},{0,1,0,0},{0,0,1,0},{0,0,0,1}},
Matrix.identity(4));
}
@Test
public void getColumn(){
assertArrayEquals(
new double[]{2,3,4,1},
Matrix.getColumn(new double[][]{{1,2,3,4},{2,3,4,1},{3,4,1,2},{4,1,2,3}}, 1),
0.0
);
}
}

44
test/zutil/ml/LinearRegressionTest.java Executable file
View file

@ -0,0 +1,44 @@
package zutil.ml;
import org.junit.Test;
import static org.junit.Assert.*;
/**
* Test cases are from the Machine Learning course on coursera.
* https://www.coursera.org/learn/machine-learning/discussions/all/threads/0SxufTSrEeWPACIACw4G5w
*/
public class LinearRegressionTest {
@Test
public void calculateHypotesis() {
double[][] hypotesis = LinearRegression.calculateHypotesis(
/* x */ new double[][]{{1, 2}, {1, 3}, {1, 4}, {1, 5}},
/* theta */ new double[]{0.1, 0.2}
);
assertArrayEquals(new double[][]{{0.5}, {0.7}, {0.9}, {1.1}}, hypotesis);
}
@Test
public void calculateCost() {
double cost = LinearRegression.calculateCost(
/* x */ new double[][]{{1, 2}, {1, 3}, {1, 4}, {1, 5}},
/* y */ new double[]{7, 6, 5, 4},
/* theta */ new double[]{0.1, 0.2}
);
assertEquals(11.9450, cost, 0.0001);
}
@Test
public void gradientAscent() {
double[] theta = LinearRegression.gradientAscent(
/* x */ new double[][]{{1, 5},{1, 2},{1, 4},{1, 5}},
/* y */ new double[]{1, 6, 4, 2},
/* theta */ new double[]{0, 0},
/* alpha */0.01);
assertArrayEquals(new double[]{0.032500, 0.107500}, theta, 0.000001);
}
}