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from sklearn.linear_model import LogisticRegression | |
from sklearn.feature_extraction.text import TfidfVectorizer | |
def train_classifier(dummy_data): | |
vectorizer = TfidfVectorizer() | |
train_texts, train_labels = zip(*dummy_data) | |
train_vectors = vectorizer.fit_transform(train_texts) | |
classifier = LogisticRegression() | |
classifier.fit(train_vectors, train_labels) | |
return classifier, vectorizer | |
def classify_text(text: str, classifier, vectorizer) -> str: | |
try: | |
transformed_data = vectorizer.transform([text]) | |
category = classifier.predict(transformed_data)[0] | |
return category | |
except Exception as e: | |
return str(e) | |