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bf2efad3f4 Full solution 2021-04-26 16:59:06 +02:00
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import gensim as gensim
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.naive_bayes import GaussianNB, MultinomialNB
from stop_words import get_stop_words
import os
import pandas as pd
def read_train_file(inDirectory):
colnames = ['Y', 'X']
df_train = pd.read_csv(inDirectory, sep="\t", names=colnames)
return df_train
def read_evaluate_file(inDirectory):
colnames = ['X']
df_evaulate = pd.read_csv(inDirectory, sep="\n", names=colnames)
return df_evaulate
def naivBayersWithTFIDFTrain(inDirectory):
df_train = read_train_file(inDirectory)
train_vectorized_corpus = vectorizer.fit_transform(df_train['X'])
gnb.fit(train_vectorized_corpus, df_train['Y'])
def naivBayersWithTFIDFEvaluate(inDirectory, outDirectory):
df_evaluate = read_evaluate_file(inDirectory)
evaluate_vectorized_corpus = vectorizer.transform(df_evaluate['X'])
evaluate = gnb.predict(evaluate_vectorized_corpus)
with open(outDirectory, 'w') as file:
for e in evaluate:
file.write("%i\n" % e)
vectorizer = TfidfVectorizer(stop_words=get_stop_words('polish'))
gnb = MultinomialNB()
naivBayersWithTFIDFTrain("train/train.tsv")
naivBayersWithTFIDFEvaluate("dev-0/in.tsv", "dev-0/out.tsv")
naivBayersWithTFIDFEvaluate("test-A/in.tsv", "test-A/out.tsv")
os.system("./geval -t dev-0")

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