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+/**
+ * @file trainMSVMMaj.c
+ * @author Gertjan van den Burg
+ * @date August, 2013
+ * @brief Command line interface for training a single model with MSVMMaj
+ *
+ * @details
+ * This is a command line program for training a single model on a given
+ * dataset. To run a grid search over a number of parameter configurations,
+ * see trainMSVMMajdataset.c.
+ *
+ */
+
+#include <time.h>
+#include <math.h>
+
+#include "msvmmaj_kernel.h"
+#include "libMSVMMaj.h"
+#include "msvmmaj.h"
+#include "msvmmaj_io.h"
+#include "msvmmaj_init.h"
+#include "msvmmaj_train.h"
+#include "util.h"
+
+#define MINARGS 2
+
+extern FILE *MSVMMAJ_OUTPUT_FILE;
+
+// function declarations
+void exit_with_help();
+void parse_command_line(int argc, char **argv, struct MajModel *model,
+ char *input_filename, char *output_filename, char *model_filename);
+
+/**
+ * @brief Help function
+ */
+void exit_with_help()
+{
+ printf("This is MSVMMaj, version %1.1f\n\n", VERSION);
+ printf("Usage: trainMSVMMaj [options] training_data_file\n");
+ printf("Options:\n");
+ printf("-c coef : coefficient for the polynomial and sigmoid kernel\n");
+ printf("-d degree : degree for the polynomial kernel\n");
+ printf("-e epsilon : set the value of the stopping criterion\n");
+ printf("-g gamma : parameter for the rbf, polynomial or sigmoid "
+ "kernel\n");
+ printf("-h | -help : print this help.\n");
+ printf("-k kappa : set the value of kappa used in the Huber hinge\n");
+ printf("-l lambda : set the value of lambda (lambda > 0)\n");
+ printf("-m model_file : use previous model as seed for W and t\n");
+ printf("-o output_file : write output to file\n");
+ printf("-p p-value : set the value of p in the lp norm "
+ "(1.0 <= p <= 2.0)\n");
+ printf("-q : quiet mode (no output)\n");
+ printf("-r rho : choose the weigth specification (1 = unit, 2 = "
+ "group)\n");
+ printf("-t type: kerneltype (LINEAR=0, POLY=1, RBF=2, SIGMOID=3)\n");
+ printf("-u use_cholesky: use cholesky decomposition when using "
+ "kernels (0 = false, 1 = true). Default 0.\n");
+
+ exit(0);
+}
+
+/**
+ * @brief Main interface function for trainMSVMMaj
+ *
+ * @details
+ * Main interface for the command line program. A given dataset file is read
+ * and a MSVMMaj model is trained on this data. By default the progress of the
+ * computations are written to stdout. See for full options of the program the
+ * help function.
+ *
+ * @param[in] argc number of command line arguments
+ * @param[in] argv array of command line arguments
+ *
+ */
+int main(int argc, char **argv)
+{
+ char input_filename[MAX_LINE_LENGTH];
+ char model_filename[MAX_LINE_LENGTH];
+ char output_filename[MAX_LINE_LENGTH];
+
+ struct MajModel *model = msvmmaj_init_model();
+ struct MajData *data = msvmmaj_init_data();
+
+ if (argc < MINARGS || msvmmaj_check_argv(argc, argv, "-help")
+ || msvmmaj_check_argv_eq(argc, argv, "-h") )
+ exit_with_help();
+ parse_command_line(argc, argv, model, input_filename,
+ output_filename, model_filename);
+
+ // read data file
+ msvmmaj_read_data(data, input_filename);
+
+ // copy dataset parameters to model
+ model->n = data->n;
+ model->m = data->m;
+ model->K = data->K;
+ model->data_file = input_filename;
+
+ // initialize kernel (if necessary)
+ msvmmaj_make_kernel(model, data);
+
+ // allocate model and initialize weights
+ msvmmaj_allocate_model(model);
+ msvmmaj_initialize_weights(data, model);
+
+ // seed the random number generator (only place in programs is in
+ // command line interfaces)
+ srand(time(NULL));
+
+ if (msvmmaj_check_argv_eq(argc, argv, "-m")) {
+ struct MajModel *seed_model = msvmmaj_init_model();
+ msvmmaj_read_model(seed_model, model_filename);
+ msvmmaj_seed_model_V(seed_model, model);
+ msvmmaj_free_model(seed_model);
+ } else {
+ msvmmaj_seed_model_V(NULL, model);
+ }
+
+ // start training
+ msvmmaj_optimize(model, data);
+
+ // write_model to file
+ if (msvmmaj_check_argv_eq(argc, argv, "-o")) {
+ msvmmaj_write_model(model, output_filename);
+ note("Output written to %s\n", output_filename);
+ }
+
+ // free model and data
+ msvmmaj_free_model(model);
+ msvmmaj_free_data(data);
+
+ return 0;
+}
+
+/**
+ * @brief Parse command line arguments
+ *
+ * @details
+ * Process the command line arguments for the model parameters, and record
+ * them in the specified MajModel. An input filename for the dataset is read
+ * and if specified an output filename and a model filename for the seed
+ * model.
+ *
+ * @param[in] argc number of command line arguments
+ * @param[in] argv array of command line arguments
+ * @param[in] model initialized model
+ * @param[in] input_filename pre-allocated buffer for the input
+ * filename
+ * @param[in] output_filename pre-allocated buffer for the output
+ * filename
+ * @param[in] model_filename pre-allocated buffer for the model
+ * filename
+ *
+ */
+void parse_command_line(int argc, char **argv, struct MajModel *model,
+ char *input_filename, char *output_filename, char *model_filename)
+{
+ int i, tmp;
+ double gamma = 1.0,
+ degree = 2.0,
+ coef = 0.0;
+
+ MSVMMAJ_OUTPUT_FILE = stdout;
+
+ // parse options
+ for (i=1; i<argc; i++) {
+ if (argv[i][0] != '-') break;
+ if (++i>=argc) {
+ exit_with_help();
+ }
+ switch (argv[i-1][1]) {
+ case 'c':
+ coef = atof(argv[i]);
+ break;
+ case 'd':
+ degree = atof(argv[i]);
+ break;
+ case 'e':
+ model->epsilon = atof(argv[i]);
+ break;
+ case 'g':
+ gamma = atof(argv[i]);
+ break;
+ case 'k':
+ model->kappa = atof(argv[i]);
+ break;
+ case 'l':
+ model->lambda = atof(argv[i]);
+ break;
+ case 'm':
+ strcpy(model_filename, argv[i]);
+ break;
+ case 'o':
+ strcpy(output_filename, argv[i]);
+ break;
+ case 'p':
+ model->p = atof(argv[i]);
+ break;
+ case 'r':
+ model->weight_idx = atoi(argv[i]);
+ break;
+ case 't':
+ model->kerneltype = atoi(argv[i]);
+ break;
+ case 'u':
+ tmp = atoi(argv[i]);
+ if (!(tmp == 1 || tmp == 0))
+ fprintf(stderr, "Unknown value %i for"
+ " use_cholesky", tmp);
+ model->use_cholesky = (tmp == 1) ? true : false;
+ break;
+ case 'q':
+ MSVMMAJ_OUTPUT_FILE = NULL;
+ i--;
+ break;
+ default:
+ fprintf(stderr, "Unknown option: -%c\n",
+ argv[i-1][1]);
+ exit_with_help();
+ }
+ }
+
+ // read input filename
+ if (i >= argc)
+ exit_with_help();
+
+ strcpy(input_filename, argv[i]);
+
+ // set kernel parameters
+ switch (model->kerneltype) {
+ case K_LINEAR:
+ break;
+ case K_POLY:
+ model->kernelparam = Calloc(double, 3);
+ model->kernelparam[0] = gamma;
+ model->kernelparam[1] = coef;
+ model->kernelparam[2] = degree;
+ break;
+ case K_RBF:
+ model->kernelparam = Calloc(double, 1);
+ model->kernelparam[0] = gamma;
+ break;
+ case K_SIGMOID:
+ model->kernelparam = Calloc(double, 1);
+ model->kernelparam[0] = gamma;
+ model->kernelparam[1] = coef;
+ }
+}
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