public static void main(String[] args)throws IOException {

// load the data

Table dataSet = TableDataSetLoader.loadDataSet(new File("src/main/resources/datasets/car_plant.csv"));

Vector labels = new Vector(dataSet, "Electricity Usage");

Table reducedDataSet = dataSet.removeColumns("Electricity Usage").first(dataSet.rowCount());

DenseMatrixSet denseMatrixSet = new DenseMatrixSet(RowType.Type.DOUBLE_VECTOR, new RowBuilder(), reducedDataSet.rowCount(), 2, 1.0);

denseMatrixSet.setColumn(1, reducedDataSet.doubleColumn(0));

denseMatrixSet.duplicateColumn(1);

// assume a hypothesis of the form w0 +w1*X + w2*X^2

// initially all weights are set o zeor

NonLinearVectorPolynomial hypothesis = new NonLinearVectorPolynomial(new ScalarMonomial(0, 0.0),

new ScalarMonomial(1, 0.0),

new ScalarMonomial(2, 0.0));

// the regressor

NonLinearRegressor regressor = new NonLinearRegressor(hypothesis);

GDInput gdInput = new GDInput();

gdInput.showIterations = true;

gdInput.eta=0.001;

gdInput.errF = new MSEVectorFunction(hypothesis);

gdInput.iterationContorller = new DefaultIterativeAlgorithmController(10000,1.0e-8);

BatchGradientDescent gdSolver = new BatchGradientDescent(gdInput);

IterativeAlgorithmResult result = (IterativeAlgorithmResult) regressor.train(denseMatrixSet, labels, gdSolver);

System.out.println(result);

System.out.println("Intercept: "+hypothesis.getCoeff(0)+" slope 1: "+hypothesis.getCoeff(1) + " slope 2"+hypothesis.getCoeff(2));

}