SentimentAnalysis
(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset
Results for Base Classifiers
<table style="width:100%">
<tr>
<th>Rank</th>
<th>Word Embedding</th>
<th>Classifier</th>
<th>Accuracy</th>
<th>F1-Score</th>
</tr>
<tr>
<td>1</td>
<td>BERT Sentence Version (Mean Bert Features per Review)</td>
<td>SVM</td>
<td bgcolor="#cedc00">90.35</td>
<td>0.90</td>
</tr>
<tr>
<td>2</td>
<td>BERT Sentence Version (Mean Bert Features per Review)</td>
<td>MLP</td>
<td>90.32</td>
<td>0.90</td>
</tr>
<tr>
<td>3</td>
<td>TFIDF with Stop Words</td>
<td>SVM</td>
<td>89.59</td>
<td>0.90</td>
</tr>
</table>
Results for Deep Neural Networks
<table style="width:100%">
<tr>
<th>Rank</th>
<th>Word Embedding</th>
<th>Model</th>
<th>Accuracy</th>
</tr>
<tr>
<td>1</td>
<td>BERT TensorFlow-HUB</td>
<td>Bi-Directional LSTM</td>
<td bgcolor="#cedc00">91.34</td>
</tr>
<tr>
<td>2</td>
<td>BERT Sentence Version (Mean Bert Features per Review)</td>
<td>1-D CNN</td>
<td>85.46</td>
</tr>
</table>
