private void btnStochastic1_Click(object sender, EventArgs e)
{
var regression = new LogisticRegression();
double[,] sourceMatrix;
double[,] inputs;
double[] labels;
GetData(out sourceMatrix, out inputs, out labels);
_weight = regression.StochasticGradientAscent1(inputs.ToArray(), labels);
var aaa = sourceMatrix.Submatrix(0, sourceMatrix.GetLength(0) - 1, 1, 3);
CreateRegressPlot(graphInput, aaa, _weight);
}
private double HorseColicTest()
{
double[,] sourceMatrix;
double[,] inputs;
double[] labels;
GetData(dgvTest, out sourceMatrix, out inputs, out labels);
var regression = new LogisticRegression();
_weight = regression.StochasticGradientAscent1(inputs.ToArray(), labels);
var errorCount = 0;
for (var i = 0; i < inputs.GetLength(0); i++)
{
var output = regression.Classify(inputs.GetRow(i), _weight);
if (output != labels[i]) errorCount++;
}
var errorRate = (double)errorCount / inputs.GetLength(0);
return errorRate;
}
private void cmdTest_Click(object sender, EventArgs e)
{
var x1 = Convert.ToDouble(txtX1.Text);
var x2 = Convert.ToDouble(txtX2.Text);
var input = new[]{1, x1,x2};
var regression = new LogisticRegression();
var cls = regression.Classify(input, _weight);
var s = cls == 0.0 ? "Blue" : "Green";
MessageBox.Show("Class = " + s);
}
