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Working on bayes2

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Maciej Sobkowiak 2021-05-12 20:29:37 +02:00
parent 7ea61e7e1f
commit d4b396f3be
1 changed files with 15 additions and 5 deletions
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bayes2.py
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@ -1,7 +1,11 @@
import pandas as pd
import numpy as np
import gzip
from sklearn.pipeline import make_pipeline
from sklearn.naive_bayes import MultinomialNB
from sklearn.feature_extraction.text import TfidfVectorizer
# Read data
dev = pd.read_table('dev-0/in.tsv', error_bad_lines=False, header=None)
test = pd.read_table('test-A/in.tsv', error_bad_lines=False, header=None)
@ -11,13 +15,19 @@ y_train = []
with gzip.open('train/train.tsv.gz', 'r') as f:
for l in f:
line = l.decode('UTF-8').replace("\n", "").split("\t")
y_train.append(line[0])
X_train.append(line[1:])
y_train.append(int(line[0]))
X_train.append(str(line[1:]))
X_train = np.asanyarray(X_train)
y_train = np.asanyarray(y_train)
# Convert to unified types
X_train = np.asarray(X_train)
y_train = np.asarray(y_train)
X_dev = dev[0].values
X_test = test[0].values
print(X_dev)
print(type(y_train[0]))
print(X_train[0])
# Create model
model = make_pipeline(TfidfVectorizer(), MultinomialNB())
model.fit(X_train, y_train)