public static Map<String, List<String>> test(
String test_data_file, Classifier model, int task, Map<String, Double> idfs)
throws Exception {
System.err.println("## Testing with feature_file=" + test_data_file + " ... \n");
Map<String, List<String>> ranked_queries = new HashMap<String, List<String>>();
Learner learner = null;
if (task == 1) {
learner = new PointwiseLearner();
} else if (task == 2) {
double C = 1.0;
double gamma = 0.25;
boolean isLinearKernel = false;
learner = new PairwiseLearner(C, gamma, isLinearKernel);
} else if (task == 3) {
double C = 1.0;
double gamma = 0.25;
boolean isLinearKernel = false;
learner = new PairwiseAddedFeatures(C, gamma, isLinearKernel);
} else if (task == 4) {
/*
* @TODO: Your code here, extra credit
* */
System.err.println("Extra credit");
}
/* Step (1): construct your test feature matrix here */
TestFeatures tf = learner.extract_test_features(test_data_file, idfs);
/* Step (2): implement your prediction and ranking code here */
ranked_queries = learner.testing(tf, model);
return ranked_queries;
}
public static Classifier train(
String train_data_file, String train_rel_file, int task, Map<String, Double> idfs)
throws Exception {
System.err.println(
"## Training with feature_file ="
+ train_data_file
+ ", rel_file = "
+ train_rel_file
+ " ... \n");
Classifier model = null;
Learner learner = null;
if (task == 1) {
learner = new PointwiseLearner();
} else if (task == 2) {
double C = 1.0;
double gamma = 0.25;
// String line;
// BufferedReader reader = new BufferedReader(new FileReader("svmtemp.txt"));
// try {
// line = reader.readLine();
// C = Double.parseDouble(line);
// line = reader.readLine();
// gamma = Double.parseDouble(line);
// } catch (Exception e) {
// System.err.println("Error while getting C and gamma.");
// System.exit(1);
// }
boolean isLinearKernel = false;
learner = new PairwiseLearner(C, gamma, isLinearKernel);
} else if (task == 3) {
// boolean isLinearKernel = true;
// learner = new PairwiseAddedFeatures(isLinearKernel);
double C = 1.0;
double gamma = 0.25;
boolean isLinearKernel = false;
String line;
// BufferedReader reader = new BufferedReader(new FileReader("svmtemp.txt"));
// try {
// line = reader.readLine();
// C = Double.parseDouble(line);
// line = reader.readLine();
// gamma = Double.parseDouble(line);
// } catch (Exception e) {
// System.err.println("Error while getting C and gamma.");
// }
learner = new PairwiseAddedFeatures(C, gamma, isLinearKernel);
} else if (task == 4) {
/*
* @TODO: Your code here, extra credit
* */
System.err.println("Extra credit");
}
/* Step (1): construct your feature matrix here */
Instances data = learner.extract_train_features(train_data_file, train_rel_file, idfs);
/* Step (2): implement your learning algorithm here */
model = learner.training(data);
return model;
}
