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diff --git a/src/trainGenSVM.c b/src/trainGenSVM.c
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+++ b/src/trainGenSVM.c
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+/**
+ * @file trainGenSVM.c
+ * @author Gertjan van den Burg
+ * @date August, 2013
+ * @brief Command line interface for training a single model with GenSVM
+ *
+ * @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 trainGenSVMdataset.c. 
+ *
+ */
+
+#include <time.h>
+#include <math.h>
+
+#include "gensvm_kernel.h"
+#include "libGenSVM.h"
+#include "gensvm.h"
+#include "gensvm_io.h"
+#include "gensvm_init.h"
+#include "gensvm_train.h"
+#include "util.h"
+
+#define MINARGS 2
+
+extern FILE *GENSVM_OUTPUT_FILE;
+
+// function declarations
+void exit_with_help();
+void parse_command_line(int argc, char **argv, struct GenModel *model, 
+		char *input_filename, char *output_filename, char *model_filename);
+
+/**
+ * @brief Help function
+ */
+void exit_with_help()
+{
+	printf("This is GenSVM, version %1.1f\n\n", VERSION);
+	printf("Usage: trainGenSVM [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 trainGenSVM
+ *
+ * @details
+ * Main interface for the command line program. A given dataset file is read
+ * and a GenSVM 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 GenModel *model = gensvm_init_model();
+	struct GenData *data = gensvm_init_data();
+
+	if (argc < MINARGS || gensvm_check_argv(argc, argv, "-help") 
+			|| gensvm_check_argv_eq(argc, argv, "-h") ) 
+		exit_with_help();
+	parse_command_line(argc, argv, model, input_filename, 
+			output_filename, model_filename);
+
+	// read data file
+	gensvm_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
+	gensvm_allocate_model(model);
+	
+	// initialize kernel (if necessary)
+	gensvm_make_kernel(model, data);
+
+	// reallocate model and initialize weights
+	gensvm_reallocate_model(model, data->n, data->m);
+	gensvm_initialize_weights(data, model);
+
+	// seed the random number generator (only place in programs is in
+	// command line interfaces)
+	srand(time(NULL));
+
+	if (gensvm_check_argv_eq(argc, argv, "-m")) {
+		struct GenModel *seed_model = gensvm_init_model();
+		gensvm_read_model(seed_model, model_filename);
+		gensvm_seed_model_V(seed_model, model, data);
+		gensvm_free_model(seed_model);
+	} else {
+		gensvm_seed_model_V(NULL, model, data);
+	}
+
+	// start training
+	gensvm_optimize(model, data);
+
+	// write_model to file
+	if (gensvm_check_argv_eq(argc, argv, "-o")) {
+		gensvm_write_model(model, output_filename);
+		note("Output written to %s\n", output_filename);
+	}
+
+	// free model and data
+	gensvm_free_model(model);
+	gensvm_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 GenModel. 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 GenModel *model, 
+		char *input_filename, char *output_filename, char *model_filename)
+{
+	int i;
+	double gamma = 1.0, 
+	       degree = 2.0, 
+	       coef = 0.0;
+
+	GENSVM_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':
+				GENSVM_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;
+	}
+}