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dixitishan811/Sentimental-Analysis

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Twitter Sentiment-Analysis

Dataset being used : Sentiment 140

I. PreProcessing :

1. Remove URL
2. Remove @
3. Remove Apostrophe
4. Remove Newline
5. Replace Emoticons with suitable text
6. Remove stopwords
7. Stemming (PorterStemmer)
8. Spell Correction
9. Regex Tokenization

II. Data Training :

1. Count Vectorization
2. LinearSVC - Non Convergent
3. Gaussian RBF SVC
4. Polynomial SVC
5. Decision Trees

III. Word Embeddings :

1. Word2Vec
2. Glove
3. Count Vectorizer
4. TF-IDF Vectorizer
5. Word2Vec with TF-IDF
6. BERT
7. BERT with TF-IDF
8. GPT-2

IV. Results :

  1. Gaussian RBF
  2. Polynomial SVC
  3. DecisionTree

V. Tests:

  1. Confusion Matrix
  2. AUC-ROC
  3. Sklearn accuracy metric
  4. Precision
  5. Recall
  6. F1 Score

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