This commit is contained in:
korne 2022-05-11 20:16:48 +02:00
parent 9cb2fb2612
commit bad68dfb59

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run.py Normal file
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import os
import sklearn
import pandas as pd
from sklearn.metrics import accuracy_score
from gzip import open as open_gz
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.pipeline import make_pipeline
def evaluation(x, path_out, model):
results = model.predict(x)
with open(path_out, 'wt') as file:
for r in results:
file.write(str(r) + '\n')
train = pd.read_csv('train/train.tsv', header = None, sep = '\t', error_bad_lines = False)
x_train = train[1]
y_train = train[0]
x_dev = pd.read_csv('dev-0/in.tsv',header = None, sep = '/t',engine = 'python')
x_dev = x_dev[0]
x_test = pd.read_csv('test-A/in.tsv',header = None, sep = '/t',engine = 'python')
x_test = x_test[0]
model = make_pipeline(TfidfVectorizer(), MultinomialNB())
model.fit(x_train, y_train)
evaluation(x_dev,'dev-0/out.tsv', model)
evaluation(x_test,'test-A/out.tsv', model)