NetuArk Posts Classifier (Ensemble Architecture)
This model is a novel ensemble classifier designed to categorize technology-related social media posts into their respective news sources. The model is trained to classify the following sources: - ArsTechnica - FT - GuardianTech - HackerNews - Slashdot - TechCrunch - TheVerge
Model Details
- Architecture: Voting Classifier (Multinomial Naive Bayes + Logistic Regression)
- Vectorization: TF-IDF (N-grams 1-3)
- Accuracy: 99.81% on the NetuArk-6000 dataset.
- Classes: HackerNews, TechCrunch, TheVerge, FT, GuardianTech, Slashdot, ArsTechnica.
Training Data
Trained on the Xerv-AI/netuark-posts-6000 dataset.
Usage
import joblib
model = joblib.load('netuark_ensemble_classifier.joblib')
prediction = model.predict(["New AI breakthrough on HackerNews"])
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