Evaluate the performance of TCN and Ensemble-based models using Word2Vec to your common deep learning architectures

A. Introduction

  • A.1. Background & Motivation
  • A.2. Objectives

B. Experiment

  • B.1. Datasets
  • B.2. The Proposed Models
  • B.2.1. Temporal Convolutional Network (TCN)
  • B.2.2. Ensemble CNN-GRU
  • B.2.3. Other Models
  • B.2.4. The Models Summary with their Feature Extractions

C. Evaluation

  • C.1. Results
  • C.2. Discussion
  • C.2.1. BoW vs. Word Embedding
  • C.2.2. Random vs. Static vs. Dynamic
  • C.2.3. TCN vs. RNN Model
  • C.2.4. Ensemble vs. Single Model
  • C.2.5. The Best Performing Models

D. Conclusions and Future Work

  • D.1. Conclusions
  • D.2. Recommendation in Future Work

#tcn #text-classification #ensemble-learning #deep-learning

Deep Learning Techniques for Text Classification
1.40 GEEK