void exe_naive_bayes()
{
NaiveBayes nb = NaiveBayes();
nb.set_training_data_file(std::string("training.dat"));
nb.add_training_data("Buy cheap viagra SPAM");
nb.add_training_data("Buy cheap airlines airlines tickets HAM");
nb.add_training_data("Dear friend I am the king of Persia king SPAM");
nb.add_training_data("Hello friend I am from Persia you must be from New York HAM");
nb.add_training_data("Hi friend how are you doing I love you HAM");
nb.add_training_data("New York is a big city HAM");
nb.get_training_data();
nb.train();
std::string class_ = nb.classify(std::string("Buy cheap viagra tickets"));
std::cout << "Your message is " << class_ << std::endl;
class_ = nb.classify(std::string("Hello friend how are you"));
std::cout << "Your message is " << class_ << std::endl;
class_ = nb.classify(std::string("Dhaka is a big city"));
std::cout << "Your message is " << class_ << std::endl;
}
int mostLikely(Digit const & digit )
{
Vector<int> values(64);
for(int i = 0; i < 8; i++)
for(int j = 0; j < 8; j++)
values.append(mapColor(digit.color[i][j]));
return nb.classify(values);
}
int main(int argc, const char * argv[]) {
DataSet train = createDataSet("/Users/Hacker/Desktop/vote_train.arff.txt");
DataSet test = createDataSet("/Users/Hacker/Desktop/vote_test.arff.txt");
vector<Instance> testData = test.instances;
vector<string> className = test.labels;
long size = testData.size();
NaiveBayes *n = new NaiveBayes(train);
n->training(train);
//Learning by NaiveBayes
long correct_count = 0;
for(long i = 0; i < size; i ++)
{
double probability = 0.00;
probability = n->classify(testData[i]);
string actualclass = className[testData[i].getlabel()];
if(probability > 0.5)
{
cout<<className[0]<<" "<<actualclass<<" ";
if(className[0] == actualclass)
{
correct_count ++;
}
printf("%.16f",probability);
}
else
{
probability = 1 - probability;
cout<<className[1]<<" "<<actualclass<<" ";
if(className[1] == actualclass)
{
correct_count ++;
}
printf("%.16f",probability);
}
cout<<endl;
}
cout<<"Number Of Correct Classification:"<<correct_count<<endl;
delete n;
return 0;
}
