import os
import csv
import math
import nltk
import constant
import numpy as np
import collections
from nltk.corpus import stopwords
from nltk.stem import SnowballStemmer
from sklearn.linear_model import RidgeClassifier
from sklearn.metrics import classification_report
from sklearn.model_selection import train_test_split
nltk.download("stopwords")
stemmer = SnowballStemmer('russian')
stemmer.stopwords = stopwords.words("russian")
def get_data() -> list:
label = 0
labels = list()
messages = list()
messageGroups = list()
for names in os.listdir(constant.PATH):
with open(constant.PATH + names,
newline='',
encoding=constant.ENCODING) as csvfile:
reader = csv.reader(csvfile)
next(reader)
messageGroup = list(np.array(list(reader)[:800])[:, 4])
messageGroups.append(messageGroup)
def get_stemmer():
stemmer = SnowballStemmer('spanish')
stemmer.stopwords = set(STOP_WORDS)
return stemmer
