rename msvmmaj to gensvm

1 files changed, 139 insertions, 0 deletions

diff --git a/include/gensvm_train_dataset.h b/include/gensvm_train_dataset.h
new file mode 100644
index 0000000..299bc52
--- /dev/null
+++ b/include/gensvm_train_dataset.h
@@ -0,0 +1,139 @@
+/**
+ * @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 "globals.h"
+#include "types.h"
+
+/**
+ * @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 start_training_tt(struct Queue *q);
+void start_training_cv(struct Queue *q);
+void free_queue(struct Queue *q);
+
+void consistency_repeats(struct Queue *q, long repeats, TrainType traintype);
+
+double cross_validation(struct GenModel *model, struct GenData *data,
+	       	long folds);
+
+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);
+#endif