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dmesquita/main.py

Last active July 5, 2020 16:18
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main.py
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.metrics import precision_recall_curve, auc
categories = ["comp.graphics","sci.space"]
newsgroups_train = fetch_20newsgroups(subset='train', categories=categories)
newsgroups_test = fetch_20newsgroups(subset='test', categories=categories)
newsgroups_all = fetch_20newsgroups(subset='all', categories=categories)
vectorizer = TfidfVectorizer()
vectorizer.fit(newsgroups_all.data)
X = vectorizer.transform(newsgroups_train.data)
clf = MultinomialNB(alpha=0.1)
clf.fit(X,newsgroups_train.target)
X_predict = vectorizer.transform(newsgroups_test.data)
y_pred_scores = clf.predict_proba(X_predict)
y_true = newsgroups_test.target
precision, recall, _ = precision_recall_curve(y_true, y_pred_scores[:, -1])
auc = auc(recall, precision)
print(auc)
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