/**
* <summary>Train method for the Dummy pos tagger. The algorithm gets all possible tag list.</summary>
*
* <param name="corpus">Training data for the tagger.</param>
*/
public void Train(PosTaggedCorpus corpus)
{
var corpusTagList = corpus.GetTagList();
_tagList = new string[corpusTagList.Count];
_tagList = corpusTagList.ToArray();
}
/**
* <summary>Train method for the Naive pos tagger. The algorithm gets all possible tag list. Then counts all
* possible tags (with its counts) for each possible word.</summary>
*
* <param name="corpus">Training data for the tagger.</param>
*/
public void Train(PosTaggedCorpus corpus)
{
var map = new Dictionary <string, CounterHashMap <string> >();
for (var i = 0; i < corpus.SentenceCount(); i++)
{
var s = corpus.GetSentence(i);
for (var j = 0; j < s.WordCount(); j++)
{
var word = (PosTaggedWord)corpus.GetSentence(i).GetWord(j);
if (map.ContainsKey(word.GetName()))
{
map[word.GetName()].Put(word.GetTag());
}
else
{
var counterMap = new CounterHashMap <string>();
counterMap.Put(word.GetTag());
map[word.GetName()] = counterMap;
}
}
}
_maxMap = new Dictionary <string, string>();
foreach (var word in map.Keys)
{
_maxMap[word] = map[word].Max();
}
}
/**
* <summary>Train method for the Hmm pos tagger. The algorithm trains an Hmm from the corpus, where corpus constitutes
* as an observation array.</summary>
*
* <param name="corpus">Training data for the tagger.</param>
*/
public void Train(PosTaggedCorpus corpus)
{
var emittedSymbols = new List <string> [corpus.SentenceCount()];
for (var i = 0; i < emittedSymbols.Length; i++)
{
emittedSymbols[i] = new List <string>();
for (var j = 0; j < corpus.GetSentence(i).WordCount(); j++)
{
var word = (PosTaggedWord)corpus.GetSentence(i).GetWord(j);
emittedSymbols[i].Add(word.GetTag());
}
}
_hmm = new Hmm1 <string, Word>(corpus.GetTagList(), emittedSymbols, corpus.GetAllWordsAsArray());
}
