Text Classification Project

Built and compared multiple neural network architectures (CNN, RNN, LSTM, ANN) using the Keras framework to classify text from the COLING_2025_MGT_en dataset. Applied majority voting for final prediction and evaluated models using accuracy, precision, recall, and F1-score. Visualized results using radar charts