from bottle import (route, run, template, request, redirect) from parse import get_news, extract_next_page from db import News, session from scripts import save from classify import Classifier s = session() classifier = Classifier() mark_news = s.query(News).filter(News.label != None).all() x_title = [row.title for row in mark_news] y_lable = [row.label for row in mark_news] classifier.fit(x_title, y_lable)
import csv
import string
from classify import Classifier
def clean(s):
translator = str.maketrans("", "", string.punctuation)
return s.translate(translator)
with open('SMSSpamCollection.csv') as f:
data = list(csv.reader(f, delimiter="\t"))
X, y = [], []
for target, msg in data:
X.append(msg)
y.append(target)
X = [clean(x).lower() for x in X]
X_train, y_train, X_test, y_test = X[0:3900], y[0:3900], X[3900:], y[3900:]
test_model = Classifier()
test_model.fit(X_train, y_train)
print(test_model.score(X_test, y_test))
