public static void main(String argv[]) throws IOException {
int i, predict_probability = 0;
svm_print_string = svm_print_stdout;
// parse options
for (i = 0; i < argv.length; i++) {
if (argv[i].charAt(0) != '-') break;
++i;
switch (argv[i - 1].charAt(1)) {
case 'b':
predict_probability = atoi(argv[i]);
break;
case 'q':
svm_print_string = svm_print_null;
i--;
break;
default:
System.err.print("Unknown option: " + argv[i - 1] + "\n");
exit_with_help();
}
}
if (i >= argv.length - 2) exit_with_help();
try {
BufferedReader input = new BufferedReader(new FileReader(argv[i]));
DataOutputStream output =
new DataOutputStream(new BufferedOutputStream(new FileOutputStream(argv[i + 2])));
svm_model model = svm.svm_load_model(argv[i + 1]);
if (model == null) {
System.err.print("can't open model file " + argv[i + 1] + "\n");
System.exit(1);
}
if (predict_probability == 1) {
if (svm.svm_check_probability_model(model) == 0) {
System.err.print("Model does not support probabiliy estimates\n");
System.exit(1);
}
} else {
if (svm.svm_check_probability_model(model) != 0) {
svm_predict.info("Model supports probability estimates, but disabled in prediction.\n");
}
}
predict(input, output, model, predict_probability);
input.close();
output.close();
} catch (FileNotFoundException e) {
exit_with_help();
} catch (ArrayIndexOutOfBoundsException e) {
exit_with_help();
}
}
public static void trainModel(ActionBarActivity obj) throws IOException, ClassNotFoundException {
ArrayList<Feature> features = Globals.getAllFeatures(obj);
ArrayList<ArrayList<Double>> train = new ArrayList<ArrayList<Double>>();
ArrayList<Double> temp;
for (Feature f : features) {
temp = new ArrayList<>();
temp.add((double) f._classLabel);
temp.addAll(f._features);
train.add(temp);
}
for (Feature f : features) {
temp = new ArrayList<>();
temp.add((double) f._classLabel);
temp.addAll(f._features);
train.add(temp);
}
for (Feature f : features) {
temp = new ArrayList<>();
temp.add((double) f._classLabel);
temp.addAll(f._features);
train.add(temp);
}
for (Feature f : features) {
temp = new ArrayList<>();
temp.add((double) f._classLabel);
temp.addAll(f._features);
train.add(temp);
}
long seed = System.nanoTime();
Collections.shuffle(train, new Random(seed));
svmTrain(train);
// Printing labels to check
printModelLabels();
writeModeltoFile(obj);
}
private static void exit_with_help() {
System.err.print(
"usage: svm_predict [options] test_file model_file output_file\n"
+ "options:\n"
+ "-b probability_estimates: whether to predict probability estimates, 0 or 1 (default 0); one-class SVM not supported yet\n");
System.exit(1);
}
public static void main(String argv[]) throws IOException {
int i, predict_probability = 0;
// parse options
for (i = 0; i < argv.length; i++) {
if (argv[i].charAt(0) != '-') break;
++i;
switch (argv[i - 1].charAt(1)) {
case 'b':
predict_probability = atoi(argv[i]);
break;
default:
System.err.print("unknown option\n");
exit_with_help();
}
}
if (i >= argv.length) exit_with_help();
try {
BufferedReader input = new BufferedReader(new FileReader(argv[i]));
DataOutputStream output = new DataOutputStream(new FileOutputStream(argv[i + 2]));
svm_model model = svm.svm_load_model(argv[i + 1]);
if (predict_probability == 1)
if (svm.svm_check_probability_model(model) == 0) {
System.err.print("Model does not support probabiliy estimates\n");
System.exit(1);
}
predict(input, output, model, predict_probability);
input.close();
output.close();
} catch (FileNotFoundException e) {
exit_with_help();
} catch (ArrayIndexOutOfBoundsException e) {
exit_with_help();
}
}
private static void exit_with_help() {
System.err.print(help());
System.exit(1);
}