/**
* Name: createClassifier Goal: Evolves a fuzzy system according to given options and dataset
*
* @param train_data: the data used to compute performance of a system and provide data
* information
* @param options: the options used to control the genetic algorithm
* @return boolean: indicates if creation was successful or not
*/
public boolean createClassifier(Object train_data, String options) {
try {
this.setOptions(weka.core.Utils.splitOptions(options));
} catch (Exception e) {
this.appendError(this.getClass().getName(), "Option not recognised: " + e.getMessage());
System.out.println("option non reconnue:");
System.out.println(e.getMessage());
return false;
}
// construction du classificateur
// les options sont separee pour plus de lisibilite en cas d'erreur
Instances data = null;
if (train_data instanceof String)
data = DataLoader.loadData(null, null, (String) train_data, true, -1);
else if (train_data instanceof Instances) data = (Instances) train_data;
else {
System.out.println("train data not supported!");
this.appendError(this.getClass().getName(), "Training data format not supported");
return false;
}
this.data = data;
Coevolution ce =
new Coevolution(
data,
mutation_rate,
crossover_rate,
selection_rate,
pop_size,
num_generations,
is_binary,
selection_algorithm,
error_algorithm,
elitism_rate,
tournament_size,
classification_weight,
error_weight,
rule_number_weight,
var_per_rule_weight,
rule_count);
fs = ce.evolveSystem();
fs.setData(data);
best_fitnesses = ce.getBestFitnesses();
if (getLogLevel() > 2)
this.appendInfo(this.getClass().getName(), "Classifier was successfully created and trained");
return true;
} /*end createClassifier*/
