|
16 | 16 | */
|
17 | 17 |
|
18 | 18 | class LinearRegression {
|
19 |
| - private List<Double> dependentX = new ArrayList<Double>(); |
20 |
| - private List<Double> independentY = new ArrayList<Double>(); |
| 19 | + private ArrayList<Double> dependentX = new ArrayList<Double>(); |
| 20 | + private ArrayList<Double> independentY = new ArrayList<Double>(); |
21 | 21 | private double m;
|
22 | 22 | private double c;
|
23 | 23 |
|
24 |
| - /** |
25 |
| - * @param : X (dependent variable), Y (independent variable) as ArrayList |
26 |
| - */ |
27 |
| - LinearRegression(List<Double> dependentX, List<Double> independentY) { |
28 |
| - this.dependentX = dependentX; |
29 |
| - this.independentY = independentY; |
30 |
| - this.equate(); |
31 |
| - } |
| 24 | + /** |
| 25 | + * @param : X (dependent variable), Y (independent variable) as ArrayList |
| 26 | + */ |
| 27 | + LinearRegression(ArrayList<Double> dependentX, ArrayList<Double> independentY) { |
| 28 | + this.dependentX = dependentX; |
| 29 | + this.independentY = independentY; |
| 30 | + this.equate(); |
| 31 | + } |
32 | 32 |
|
33 |
| - private double sumation(List<Double> arr) { |
34 |
| - double sum = 0.0; |
| 33 | + private double sumation(List<Double> arr) { |
| 34 | + double sum = 0.0; |
35 | 35 |
|
36 |
| - for (int i = 0; i < arr.size(); i++) { |
37 |
| - sum += arr.get(i); |
38 |
| - } |
| 36 | + for (int i = 0; i < arr.size(); i++) { |
| 37 | + sum += arr.get(i); |
| 38 | + } |
39 | 39 |
|
40 |
| - return sum; |
41 |
| - } |
| 40 | + return sum; |
| 41 | + } |
42 | 42 |
|
43 |
| - private List<Double> multiplyNumber(List<Double> arr1, List<Double> arr2) { |
44 |
| - List<Double> temp = new ArrayList<Double>(); |
45 |
| - for (int i = 0; i < arr1.size(); i++) { |
46 |
| - temp.add((arr1.get(i) * arr2.get(i))); |
| 43 | + private List<Double> multiplyNumber(List<Double> arr1, List<Double> arr2) { |
| 44 | + List<Double> temp = new ArrayList<Double>(); |
| 45 | + for (int i = 0; i < arr1.size(); i++) { |
| 46 | + temp.add((arr1.get(i) * arr2.get(i))); |
| 47 | + } |
| 48 | + return temp; |
47 | 49 | }
|
48 |
| - return temp; |
49 |
| - } |
50 | 50 |
|
51 |
| - private void equate() { |
52 |
| - int n = dependentX.size(); |
53 |
| - this.m = (n * sumation(multiplyNumber(independentY, dependentX)) - (sumation(dependentX) * sumation(independentY))); |
54 |
| - this.m = this.m / (n * (sumation(multiplyNumber(dependentX, dependentX))) - (sumation(dependentX) * sumation(dependentX))); |
| 51 | + private void equate() { |
| 52 | + int n = dependentX.size(); |
| 53 | + this.m = (n * sumation(multiplyNumber(independentY, dependentX)) - (sumation(dependentX) * sumation(independentY))); |
| 54 | + this.m = this.m / (n * (sumation(multiplyNumber(dependentX, dependentX))) - (sumation(dependentX) * sumation(dependentX))); |
55 | 55 |
|
56 |
| - this.c = (sumation(independentY) * sumation(multiplyNumber(dependentX, dependentX)) - (sumation(dependentX) * sumation(multiplyNumber(independentY, dependentX)))); |
57 |
| - this.c = this.c / (n * (sumation(multiplyNumber(dependentX, dependentX))) - (sumation(dependentX) * sumation(dependentX))); |
58 |
| - } |
| 56 | + this.c = (sumation(independentY) * sumation(multiplyNumber(dependentX, dependentX)) - (sumation(dependentX) * sumation(multiplyNumber(independentY, dependentX)))); |
| 57 | + this.c = this.c / (n * (sumation(multiplyNumber(dependentX, dependentX))) - (sumation(dependentX) * sumation(dependentX))); |
| 58 | + } |
59 | 59 |
|
60 |
| - public double getM() { |
61 |
| - return this.m; |
62 |
| - } |
| 60 | + public double getM() { |
| 61 | + return this.m; |
| 62 | + } |
63 | 63 |
|
64 |
| - public double getC() { |
65 |
| - return this.c; |
66 |
| - } |
| 64 | + public double getC() { |
| 65 | + return this.c; |
| 66 | + } |
67 | 67 |
|
68 |
| - public double predictForX(double x) { |
69 |
| - return (this.m * x) + this.c; |
70 |
| - } |
| 68 | + public double predictForX(double x) { |
| 69 | + return (this.m * x) + this.c; |
| 70 | + } |
71 | 71 | }
|
| 72 | + |
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