article_learner.py 文件源码

def article_trainers(articles: ArticleDB):
    """
    Run repeated models against article db to predict validity score for
    articles.
    """
    models = [(DecisionTreeClassifier, {}),
              (RandomForestClassifier, {}),
              (LogisticRegression, {'C': [0.01, 0.1, 1, 10, 100]}),
              (MultinomialNB, {'alpha': [0.1, 1.0, 10.0, 100.0]}),
              (LinearSVC, {'C': [0.01, 0.1, 1, 10, 100]})]
    trained_models = []
    for classifier, param_grid in models:
        res = train_model(articles, classifier, param_grid, probabilities=True)
        trained_models.append((str(res), res))
    ensemble_learner = VotingClassifier(estimators=trained_models[:4],
                                        voting='soft')
    train_model(articles, ensemble_learner, {})