public static void RegressionChart(IList <KeyValuePair <Employee, float> > predictions, string fileName)
{
const int minValue = 1500;
const int maxValue = 6500;
PlotToFile(fileName, pl =>
{
pl.env(minValue, maxValue, minValue, maxValue, AxesScale.Equal, AxisBox.BoxTicksLabelsAxes);
pl.lab("Actual", "Predicted", "Distribution of Salary Prediction");
pl.col0(Blue);
foreach (var(employee, prediction) in predictions)
{
var x = employee.Salary;
var y = prediction;
pl.poin(new double[] { x }, new double[] { y }, Dot);
}
var points = predictions.Select(p => ((float)p.Key.Salary, p.Value)).ToList();
StatisticsService.CalculateRegressionLine(points, minValue, maxValue, out var y1, out var y2);
pl.col0(Red);
pl.line(new double[] { minValue, maxValue }, new double[] { y1, y2 });
});
public void It_should_return_the_correct_result_of_a_more_complex_problem()
{
var points = new List <(float x, float y)> {
(-2, -3), (-1, -1), (1, 2), (4, 3)
};
StatisticsService.CalculateRegressionLine(points, -10, 32, out var y1, out var y2);
// y = 41x/42 - 5/21
y1.ShouldBe(-10, .0001);
y2.ShouldBe(31, .0001);
}
public void It_should_return_the_correct_result()
{
var points = new List <(float x, float y)> {
(1, 2), (2, 1), (4, 3)
};
StatisticsService.CalculateRegressionLine(points, 0, 7, out var y1, out var y2);
y1.ShouldBe(1, .0001);
y2.ShouldBe(4, .0001);
}
public static void RegressionChart(IList <Employee> employees, string fileName)
{
const int minValueX = 20;
const int maxValueX = 60;
const int minValueY = 1500;
const int maxValueY = 6500;
PlotToFile(fileName, pl =>
{
pl.env(minValueX, maxValueX, minValueY, maxValueY, AxesScale.Independent, AxisBox.BoxTicksLabelsAxes);
pl.lab("Age", "Salary", "Regression of Salary");
void Plot(ExperienceLevel experienceLevel, int color)
{
var list = employees.Where(e => e.ExperienceLevel == experienceLevel).Take(100);
var points = list.Select(employee => ((float)employee.Age, (float)employee.Salary)).ToList();
pl.col0(color);
points.ForEach(p => pl.poin(new double[] { p.Item1 }, new double[] { p.Item2 }, Dot));
pl.col0(color);
StatisticsService.CalculateRegressionLine(points, minValueX, maxValueX, out var y1, out var y2);
pl.line(new double[] { minValueX, maxValueX }, new double[] { y1, y2 });
}