1 files changed, 0 insertions, 244 deletions
diff --git a/src/trainMSVMMaj.c b/src/trainMSVMMaj.c
deleted file mode 100644
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--- a/src/trainMSVMMaj.c
+++ /dev/null
@@ -1,244 +0,0 @@
-/**
- * @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");
-
-	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;
-	
-	// allocate model
-	msvmmaj_allocate_model(model);
-	
-	// initialize kernel (if necessary)
-	msvmmaj_make_kernel(model, data);
-
-	// reallocate model and initialize weights
-	msvmmaj_reallocate_model(model, data->n, data->m);
-	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, data);
-		msvmmaj_free_model(seed_model);
-	} else {
-		msvmmaj_seed_model_V(NULL, model, data);
-	}
-
-	// 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;
-	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 '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;
-	}
-}