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  This dataset is designed for a Text Classification to be specific Multi Class Classification, inorder to train a model (Supervised Learning) for Sentiment Analysis.
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  <br>
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  Also to be able retrain the model on the given feedback over a wrong predicted sentiment this dataset will help to manage those things using **Other Features**.
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- <br>
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  **Main Features**
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  | text | labels |
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  |----------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------|
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  | This feature variable has all sort of texts, sentences, tweets, etc. | This target variable contains 3 types of numeric values as sentiments such as 0, 1 and 2. Where 0 means Negative, 1 means Neutral and 2 means Positive. |
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- <br>
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-
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  **Other Features**
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  | preds | feedback | retrain_labels | retrained_preds |
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  |----------------------------------------------------------|--------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------|
 
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  This dataset is designed for a Text Classification to be specific Multi Class Classification, inorder to train a model (Supervised Learning) for Sentiment Analysis.
19
  <br>
20
  Also to be able retrain the model on the given feedback over a wrong predicted sentiment this dataset will help to manage those things using **Other Features**.
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+
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  **Main Features**
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  | text | labels |
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  |----------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------|
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  | This feature variable has all sort of texts, sentences, tweets, etc. | This target variable contains 3 types of numeric values as sentiments such as 0, 1 and 2. Where 0 means Negative, 1 means Neutral and 2 means Positive. |
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  **Other Features**
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  | preds | feedback | retrain_labels | retrained_preds |
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  |----------------------------------------------------------|--------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------|