int main(void) {
double data[][4] = {
{3.5, 5.3, 0.2, -1.2},
{4.4, 2.2, 0.3, 0.4},
{1.3, 0.5, 4.1, 3.2}
};
int labels[] = {1, 2, 3};
Classifier* logReg = new LogisticRegression();
logReg->epsilon = 1e-5;
logReg->feedData<4>(data, 3, 4);
logReg->feedLabels(labels, 3);
// Get elapsed time in seconds
tic();
logReg->train();
fprintf("Elapsed time: %.3f seconds.\n", toc());
fprintf("W:\n");
printMatrix(*logReg->W);
fprintf("b:\n");
printVector(logReg->b, 3);
// double** dataTest = data;
double dataTest[][4] = {
{3.5, 5.3, 0.2, -1.2},
{4.4, 2.2, 0.3, 0.4},
{1.3, 0.5, 4.1, 3.2}
};
fprintf("Ground truth:\n");
printMatrix(*logReg->Y);
fprintf("Predicted probability matrix:\n");
Matrix& Prob_pred = logReg->predictLabelScoreMatrix<4>(dataTest, 3, 4);
disp(Prob_pred);
fprintf("Predicted label matrix:\n");
Matrix& Y_pred = logReg->predictLabelMatrix<4>(dataTest, 3, 4);
printMatrix(Y_pred);
int* pred_labels = logReg->predict(dataTest, 3, 4);
Classifier::getAccuracy(pred_labels, labels, 3);
tic();
std::string trainDataFilePath = "heart_scale";
logReg = new LogisticRegression();
DataSet& dataSet = readDataSetFromFile(trainDataFilePath);
logReg->feedData(*dataSet.X);
logReg->feedLabels(dataSet.Y, dataSet.nExample);
logReg->train();
Matrix& XTest = *dataSet.X;
pred_labels = logReg->predict(XTest);
int nt = XTest.getRowDimension();
Classifier::getAccuracy(pred_labels, logReg->labels, nt);
fprintf("Elapsed time: %.3f seconds.\n", toc());
return EXIT_SUCCESS;
}
