Esempio n. 1
0
from corpus import get_data, get_lexicon
from hmm import get_HMM
from viterbi import decode
from evaluation import eval_model
import random

train_set = get_data("corpus.xml")[:]
lexicon = get_lexicon("lexicon.txt")
model = get_HMM(train_set, lexicon)

results = eval_model(train_set, model)

print("\nworst_tags\n", results["worst_tags"])
print("\nworst_words:\n", results["worst_words"])
print("\nacc: ", results["accuracy"])
#print("confusion matrix:")
#print(results["confusion"].tabulate())
from corpus import get_data  #,get_lexicon
from hmm import get_HMM
from viterbi import decode
from evaluation import eval_model
import random

train_set = get_data("corpus.xml")[:50]
model = get_HMM(train_set)

results = eval_model(train_set, model)

print("\nworst_tags\n", results["worst_tags"])
print("\nworst_words:\n", results["worst_words"])
print("\nacc: ", results["accuracy"])
print("confusion matrix:")
print(results["confusion"].tabulate())