Add new Main function for new Dataset

src/main/java/be/cylab/java/wowa/training/Icmcis.java

+package be.cylab.java.wowa.training;
+
+import java.util.logging.Level;
+import java.util.logging.Logger;
+import java.util.logging.SimpleFormatter;
+import java.util.logging.StreamHandler;
+
+public class Icmcis {
+
+
+    public static void main(final String[] args) {
+
+
+        int population_size = Integer.parseInt(args[0]);
+        int crossover_rate = Integer.parseInt(args[1]);
+        int mutation_rate = Integer.parseInt(args[2]);
+        int max_generation_number = Integer.parseInt(args[3]);
+        int selection_method;
+        if (args[4].matches("RWS")) {
+            selection_method = TrainerParameters.SELECTION_METHOD_RWS;
+        } else if (args[4].matches("TOS")) {
+            selection_method = TrainerParameters.SELECTION_METHOD_TOS;
+        } else {
+            throw new IllegalArgumentException(
+                    "Selection method must be RWS ar TOS");
+        }
+        int generation_population_method;
+        if (args[5].matches("RANDOM")) {
+            generation_population_method
+                    = TrainerParameters.POPULATION_INITIALIZATION_RANDOM;
+        } else if (args[5].matches("QUASI_RANDOM")) {
+            generation_population_method
+                    = TrainerParameters.POPULATION_INITIALIZATION_QUASI_RANDOM;
+        } else {
+            throw new IllegalArgumentException(
+                    "Initialization must be RANDOM or QUASI_RANDOM");
+        }
+        String solution_type = args[6];
+        AbstractSolution sol_type = null;
+        if (solution_type.matches("DISTANCE")) {
+            sol_type = new SolutionDistance(16);
+        } else if (solution_type.matches("AUC")) {
+            sol_type = new SolutionAUC(16);
+        } else {
+            throw new IllegalArgumentException(
+                    "Solution type must be Distance or AUC");
+        }
+
+        String data_file = "./ressources/ratio_train.csv";
+        String expected_file
+                = "./ressources/Label.csv";
+        Logger logger = Logger.getLogger(Trainer.class.getName());
+        logger.setLevel(Level.INFO);
+        StreamHandler handler = new StreamHandler(System.out,
+                new SimpleFormatter());
+        logger.addHandler(handler);
+        TrainerParameters parameters = new TrainerParameters(
+                logger, population_size,
+                crossover_rate,
+                mutation_rate,
+                max_generation_number,
+                selection_method,
+                generation_population_method);
+        Trainer trainer = new Trainer(parameters, sol_type);
+
+        AbstractSolution result = trainer.runCSV(data_file, expected_file);
+        System.out.println(result);
+    }
+}