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diff --git a/include/gensvm_train_dataset.h b/include/gensvm_train_dataset.h
deleted file mode 100644
index 9a3fe86..0000000
--- a/include/gensvm_train_dataset.h
+++ /dev/null
@@ -1,143 +0,0 @@
-/**
- * @file gensvm_train_dataset.h
- * @author Gertjan van den Burg
- * @date August, 2013
- * @brief Structs and functions necessary for the grid search
- *
- * @details
- * The grid search for the optimal parameters is done through a queue.
- * This file contains struct definitions for this queue and a single
- * task in a queue, as well as a structure for the complete training
- * scheme. Function declarations are also included.
- *
- */
-
-#ifndef GENSVM_TRAIN_DATASET_H
-#define GENSVM_TRAIN_DATASET_H
-
-#include "types.h"
-
-// forward declarations
-struct GenData;
-struct GenModel;
-
-/**
- * @brief A structure for a single task in the queue.
- *
- * @param folds 	number of folds in cross validation
- * @param ID 		numeric id of the task in the queue
- * @param weight_idx 	parameter for the GenModel
- * @param p 		parameter for the GenModel
- * @param kappa 	parameter for the GenModel
- * @param lambda 	parameter for the GenModel
- * @param epsilon 	parameter for the GenModel
- * @param kerneltype 	parameter for the GenModel
- * @param *kernelparam parameters for the GenModel
- * @param *train_data 	pointer to the training data
- * @param *test_data 	pointer to the test data (if any)
- * @param performance 	performance after cross validation
- */
-struct Task {
-	KernelType kerneltype;
-	int weight_idx;
-	long folds;
-	long ID;
-	double p;
-	double kappa;
-	double lambda;
-	double epsilon;
-	double *kernelparam;
-	struct GenData *train_data;
-	struct GenData *test_data;
-	double performance;
-};
-
-/**
- * @brief Simple task queue.
- *
- * This struct is basically just an array of pointers to Task instances,
- * with a length and an index of the current task.
- *
- * @param **tasks 	array of pointers to Task structs
- * @param N 		size of task array
- * @param i 		index used for keeping track of the queue
- */
-struct Queue {
-	struct Task **tasks;
-	long N;
-	long i;
-};
-
-/**
- * @brief Structure for describing the entire grid search
- *
- * @param traintype 		type of training to use
- * @param kerneltype 		type of kernel to use throughout training
- * @param repeats 		number of repeats to be done after the grid
- * 				search to find the parameter set with the
- * 				most consistent high performance
- * @param folds 		number of folds in cross validation
- * @param Np 			size of the array of p values
- * @param Nl 			size of the array of lambda values
- * @param Nk 			size of the array of kappa values
- * @param Ne 			size of the array of epsilon values
- * @param Nw 			size of the array of weight_idx values
- * @param Ng 			size of the array of gamma values
- * @param Nc 			size of the array of coef values
- * @param Nd 			size of the array of degree values
- * @param *weight_idxs 		array of weight_idxs
- * @param *ps 			array of p values
- * @param *lambdas 		array of lambda values
- * @param *kappas 		array of kappa values
- * @param *epsilons 		array of epsilon values
- * @param *gammas 		array of gamma values
- * @param *coefs 		array of coef values
- * @param *degrees 		array of degree values
- * @param *train_data_file 	filename of train data file
- * @param *test_data_file 	filename of test data file
- *
- */
-struct Training {
-	TrainType traintype;
-	KernelType kerneltype;
-	long repeats;
-	long folds;
-	long Np;
-	long Nl;
-	long Nk;
-	long Ne;
-	long Nw;
-	long Ng;
-	long Nc;
-	long Nd;
-	int *weight_idxs;
-	double *ps;
-	double *lambdas;
-	double *kappas;
-	double *epsilons;
-	double *gammas;
-	double *coefs;
-	double *degrees;
-	char *train_data_file;
-	char *test_data_file;
-};
-
-void make_queue(struct Training *training, struct Queue *queue,
-		struct GenData *train_data, struct GenData *test_data);
-
-struct Task *get_next_task(struct Queue *q);
-void free_queue(struct Queue *q);
-
-void consistency_repeats(struct Queue *q, long repeats, TrainType traintype);
-
-void make_model_from_task(struct Task *task, struct GenModel *model);
-void copy_model(struct GenModel *from, struct GenModel *to);
-
-void print_progress_string(struct Task *task, long N);
-
-// new
-void start_training(struct Queue *q);
-double gensvm_cross_validation(struct GenModel *model,
-	       	struct GenData **train_folds, struct GenData **test_folds,
-		int folds, long n_total);
-#endif