//   file : train_hmm.cc// version: 1.03 [August 21, 1995]///*  Copyright (C) 1994 Richard Myers and James Whitson  Permission is granted to any individual or institution to use, copy, or  redistribute this software so long as all of the original files are   included unmodified, that it is not sold for profit, and that this   copyright notice is retained.*/// This program creates a hidden markov model from a series of symbol sequences// using an initial predefined model or randomly generated model.#include <stdio.h>#include <stdlib.h>#include <iostream.h>#include <fstream.h>#include <string.h>#include "hmm.h"main(int argc, char* argv[]){  // get command line parms  char* train_file=argv[1];  char* initial_model;  double min_delta_psum;  int states,symbols,seed;  // check args  if (argc != 4 && argc != 6) {    cerr << "ERROR: Too few arguments.\n\n" <<     "Usage: "<< argv[0]<<" <train_file> <hmm_model> <min_delta_psum> or \n" <<    "       "<< argv[0]<<" <train_file> <seed> <nstates> <nsymbols> <min_delta_psum>\n\n";    exit (-1);  }    if (argc==4) {    initial_model=argv[2];    min_delta_psum=atof(argv[3]);  }  if (argc==6) {    seed = atoi(argv[2]);    states = atoi(argv[3]);    symbols = atoi(argv[4]);    min_delta_psum=atof(argv[5]);  }  HMM *hmm;  if (argc==4) {    // initialize model from model file    hmm = new HMM(initial_model);    // train model on data    hmm->batch_train(train_file,min_delta_psum);  }  else {    // initialize model randomly    hmm = new HMM(symbols, states, seed);    // train model on data    hmm->batch_train(train_file,min_delta_psum);  }    // dump the resulting model to a file  char newfilename[100];  sprintf(newfilename,"%s.hmm",train_file);  hmm->dump_model(newfilename);    delete hmm;}