MultiClassTsetlinMachineBits.c

/*

Copyright (c) 2019 Ole-Christoffer Granmo

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SOFTWARE.

This code implements a multiclass version of the Tsetlin Machine from paper arXiv:1804.01508
https://arxiv.org/abs/1804.01508

*/

#include <stdio.h>
#include <stdlib.h>

#include "MultiClassTsetlinMachineBits.h"

/**************************************/
/*** The Multiclass Tsetlin Machine ***/
/**************************************/

/*** Initialize Tsetlin Machine ***/
struct MultiClassTsetlinMachine *CreateMultiClassTsetlinMachine()
{

	struct MultiClassTsetlinMachine *mc_tm;

	mc_tm = (void *)malloc(sizeof(struct MultiClassTsetlinMachine));

	for (int i = 0; i < CLASSES; i++) {
		mc_tm->tsetlin_machines[i] = CreateTsetlinMachine();
	}
	return mc_tm;
}

void mc_tm_initialize(struct MultiClassTsetlinMachine *mc_tm)
{
	for (int i = 0; i < CLASSES; i++) {
		tm_initialize(mc_tm->tsetlin_machines[i]);
	}
}

/********************************************/
/*** Evaluate the Trained Tsetlin Machine ***/
/********************************************/

float mc_tm_evaluate(struct MultiClassTsetlinMachine *mc_tm, unsigned int X[][LA_CHUNKS], int y[], int number_of_examples)
{
	int errors;
	int max_class;
	int max_class_sum;

	errors = 0;
	for (int l = 0; l < number_of_examples; l++) {
		/******************************************/
		/*** Identify Class with Largest Output ***/
		/******************************************/

		max_class_sum = tm_score(mc_tm->tsetlin_machines[0], X[l]);
		max_class = 0;
		for (int i = 1; i < CLASSES; i++) {	
			int class_sum = tm_score(mc_tm->tsetlin_machines[i], X[l]);
			if (max_class_sum < class_sum) {
				max_class_sum = class_sum;
				max_class = i;
			}
		}

		if (max_class != y[l]) {
			errors += 1;
		}
	}
	
	return 1.0 - 1.0 * errors / number_of_examples;
}

/******************************************/
/*** Online Training of Tsetlin Machine ***/
/******************************************/

// The Tsetlin Machine can be trained incrementally, one training example at a time.
// Use this method directly for online and incremental training.

void mc_tm_update(struct MultiClassTsetlinMachine *mc_tm, unsigned int Xi[], int target_class, float s)
{
	tm_update(mc_tm->tsetlin_machines[target_class], Xi, 1, s);

	// Randomly pick one of the other classes, for pairwise learning of class output 
	unsigned int negative_target_class = (unsigned int)CLASSES * 1.0*rand()/((unsigned int)RAND_MAX + 1);
	while (negative_target_class == target_class) {
		negative_target_class = (unsigned int)CLASSES * 1.0*rand()/((unsigned int)RAND_MAX + 1);
	}
	tm_update(mc_tm->tsetlin_machines[negative_target_class], Xi, 0, s);
}

/**********************************************/
/*** Batch Mode Training of Tsetlin Machine ***/
/**********************************************/

void mc_tm_fit(struct MultiClassTsetlinMachine *mc_tm, unsigned int X[][LA_CHUNKS], int y[], int number_of_examples, int epochs, float s)
{
	for (int epoch = 0; epoch < epochs; epoch++) {
		// Add shuffling here...		
		for (int i = 0; i < number_of_examples; i++) {
			mc_tm_update(mc_tm, X[i], y[i], s);
		}
	}
}