Final

Author: augusto-marques-pt

ProjetoAMC/src/Classifier.java

@@ -43,7 +43,7 @@ public int classify(int[] amostra) {
 				erro = true;
 			}
 		}
-		//System.out.println(odds.toString());
+		//System.out.println(odds.toString()); // para ver probabilidades ao correr testes
 		if (erro) return r;
 		else { throw new AssertionError("Erro");} 
 	}

ProjetoAMC/src/Dataset.java

@@ -4,7 +4,7 @@
 
 public class Dataset implements Serializable{
 	//default serialVersion id
-    private static final long serialVersionUID = 1L;
+    private static final long serialVersionUID = 1L; 
 
 	protected ArrayList<int[]> data; // lista de amostras (dados)
 	private int n; // numero de variaveis aleatorias, o java comeca a contar do 0

ProjetoAMC/src/JanelaAprendizagem.java

@@ -91,7 +91,7 @@ public ArrayList<MRFTree> ChowLiu(Dataset ds) {
 		return mrftList;
 
 	}
-	//TODO delete?
+	
 	public void testes_old(Dataset ds, Classifier classificador, int limit) {
 		System.out.println(classificador);
 
@@ -106,9 +106,9 @@ public void testes_old(Dataset ds, Classifier classificador, int limit) {
 			if (result) rtests++;
 			System.out.println("" + result + ", expected = " + expected + ", predicted = " + predicted);
 		}
-		System.out.println("Finished. " + rtests + "/" + Math.min(limit, ds.getData().size()));
+		System.out.println("Finished. " + rtests + "/" + Math.min(limit, ds.getData().size()) + "=" + rtests*100/Math.min(limit, ds.getData().size()));
 	}
-	//TODO delete?
+	
 	public void testes(Dataset ds, int limit) {		
 		System.out.println("Beginning tests...");
 		int rtests = 0;
@@ -132,9 +132,8 @@ public void testes(Dataset ds, int limit) {
 
 			ds.Add(sample);
 		}
-		
-		System.out.println("Finished. " + rtests + "/" + Math.min(limit, ds.getData().size()));
-	}
+		System.out.println("Finished. " + rtests + "/" + Math.min(limit, ds.getData().size()) + " = " + Double.valueOf(rtests)*100/Double.valueOf(Math.min(limit, ds.getData().size())) + "%");
+	} 
 
 	// Initialize the contents of the frame.
 
@@ -205,7 +204,7 @@ public void mouseClicked(MouseEvent e) {
 
 				Classifier classificador = new Classifier(mrftList, ds.Freqlist); 
 
-				lblStatus.setText(lblStatus.getText().substring(0, lblStatus.getText().length()-7)  + "Saving the model </html>");
+				lblStatus.setText(lblStatus.getText().substring(0, lblStatus.getText().length()-7)  + "Saving the model. </html>");
 
 				String savePath = txtSavePath.getText();
 
@@ -258,7 +257,6 @@ public void mouseClicked(MouseEvent e) {
 
 		txtDsPath.setBounds(48, 43, 253, 26);
 		frmJanelaAprendizagem.getContentPane().add(txtDsPath);
-		//txtDsPath.setText("/Users/miguelfernandes/Documents/GitHub/amc/Datasets2021/bcancer.csv"); // TODO comentar e apagar no fim
 		txtDsPath.setColumns(10);
 
 		JLabel lblNewLabel = new JLabel("Dataset path");
@@ -281,7 +279,6 @@ public void mouseClicked(MouseEvent e) {
 		});
 		txtSavePath.setBounds(48, 109, 253, 26);
 		frmJanelaAprendizagem.getContentPane().add(txtSavePath);
-		//txtSavePath.setText("/Users/miguelfernandes/Documents/GitHub/amc/Models2021/bcancer.ser"); // TODO comentar e apagar no fim
 		txtSavePath.setColumns(10);
 
 		JLabel lblNewLabel_1 = new JLabel("Save path for the model");

ProjetoAMC/src/JanelaClassificador.java

@@ -98,7 +98,6 @@ public void mouseClicked(MouseEvent e) {
 		            // e necessario usar um cast (Classifier) para definir qual vai ser a classe do objeto que vai ser lido
 		            classificador = (Classifier) objectIn.readObject();
 
-		            //System.out.println("The Classifier model has been read from the file");
 		            lblModelStatus.setText("Model loaded!");
 
 		            objectIn.close();

ProjetoAMC/src/WeightedGraph.java

@@ -6,7 +6,7 @@ public class WeightedGraph { // grafo pesado
 		private int dim;
 		private double[][] ma;
 
-		public WeightedGraph(int dim) { // metodo construtor
+		public WeightedGraph(int dim) { 
 			this.dim = dim;
 			this.ma = new double[dim][dim];
 
@@ -120,7 +120,7 @@ public Tree MST(int r) {  // determina a MST com o Algoritmo de Prim,
 		// metodo auxiliar para o metodo MST
 		public int ExtractMin(Queue<Integer> Q, double[] C) {
 			double min = Double.POSITIVE_INFINITY;
-			int r = 0; // o java obriga a que a variavel seja iniciada
+			int r = 0; 
 			for (int i : Q) {
 				if (C[i] < min) {
 					min = C[i];