public void TestLinearRegression()
{
double [][] inputs = new double[3][];
inputs[0] = new double[3];
inputs[1] = new double[3];
inputs[2] = new double[3];
/*
* system of equations:
* x1 + x2 + x3 = 35
* x1 + x2 - x3 = -13
* x1 - x2 + x3 = 19
*
* x1 should be 3, x2 should be 8, x3 should be 24
*
*/
inputs[0][0] = 1;
inputs[0][1] = 1;
inputs[0][2] = 1;
inputs[1][0] = 1;
inputs[1][1] = 1;
inputs[1][2] = -1;
inputs[2][0] = 1;
inputs[2][1] = -1;
inputs[2][2] = 1;
double [] outputs = new double[3];
outputs[0] = 35;
outputs[1] = -13;
outputs[2] = 19;
var normalizer = new MultiThreadedNormalization();
var regressor = new LinearRegressor(normalizer, epsilon: 0.0000001);
var matrix = new Matrix(inputs);
var weights = regressor.Fit(matrix, outputs);
var inputs2 = new double[1][];
inputs2[0] = new double[3];
inputs2[0][0] = 2;
inputs2[0][1] = 2;
inputs2[0][2] = 2;
var inputMatrix = new Matrix(inputs2);
var result = regressor.Predict(inputMatrix);
}
private static void LinearRegression()
{
Console.WriteLine("Fetching data . . .");
var data = Queries.GetData();
Console.WriteLine("Preprocessing data for linear regression . . .");
var train = (int)(data.Count * 0.9);
var lr = new LinearRegressor(5);
for (var i = 0; i < train; ++i)
{
var x = new double[5]
{
Location.ToDistance(data[i].Get("Deo Grada")),
Convert.ToDouble(data[i].Get("Kvadratura")?.Split(' ')[0] ?? "0") / 100000,
Convert.ToDouble(data[i].Get("Godina izgradnje") ?? "0") / 2020,
Convert.ToDouble(data[i].Get("Ukupan broj soba") ?? "0") / 1000,
Convert.ToDouble(data[i].Get("Ukupan broj spratova") ?? "0") / 500
};
lr.Add(x, Convert.ToDouble(data[i].Price));
}
Console.WriteLine("Training linear regressor . . .");
lr.Train(LinearRegressor.MSE, 1e-6, 10000);
Console.WriteLine("Test\t\tTrue\t\t\tPredicted");
for (var i = train; i < data.Count; ++i)
{
var x = new double[5]
{
Location.ToDistance(data[i].Get("Deo Grada")),
Convert.ToDouble(data[i].Get("Kvadratura")?.Split(' ')[0] ?? "0") / 100000,
Convert.ToDouble(data[i].Get("Godina izgradnje") ?? "0") / 2020,
Convert.ToDouble(data[i].Get("Ukupan broj soba") ?? "0") / 1000,
Convert.ToDouble(data[i].Get("Ukupan broj spratova") ?? "0") / 500
};
var yh = lr.Predict(x);
Console.WriteLine($"{i - train + 1}:\t\t{data[i].Price:F2}\t\t{yh:F2}");
}
}