Assignments of Coursera National Language Processing by Michael Collins Columbia University ---- H1: Hidden Markov Models ---- Instruction refer to h1/h1.pdf hmm.py Hmm_ex, extending Hmm, calculates and stores: * e(x|y), * q(y_i|y_i-1, y_i-2) * count(x), * rare_word, * all tags * all words SimpleTagger does simple tagging as instructed by Part 1 ViterbiTagger does Viterbi tagging as instructed by Part 2 p1.py Part 1 p2.py Part 2 p3.py Part 3 not as good as required: Your F1-Score is 35.009 and the goal F1-Score is 39.519. util.py Helper methods including * handling rare word (applying different rules) * test data iterator
rake93/Coursera_NLP_MC
Coursera Natural Language Processing by Michael Collins Columbia University
Python