Duplicate from prasadsawant7/sentiment_analysis_preprocessed_dataset

Co-authored-by: Prasad Sawant <prasadsawant7@users.noreply.huggingface.co>

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README.md

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+---
+license: mit
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- sentiment-analysis
+- text-classification
+- multiclass-classification
+pretty_name: Sentiment Analysis Preprocessed Dataset including training and testing split
+size_categories:
+- 10K<n<100K
+---
+
+**Brief idea about dataset**:
+<br>
+This dataset is designed for a Text Classification to be specific Multi Class Classification, inorder to train a model (Supervised Learning) for Sentiment Analysis.
+<br>
+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**.
+
+
+**Main Features**
+| text                                                                 | labels                                                                                                                                                  |
+|----------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------|
+| 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. |
+
+**Other Features**
+| preds                                                    | feedback                                                                                               | retrain_labels                                                                                 | retrained_preds                                                              |
+|----------------------------------------------------------|--------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------|
+| In this variable all predictions are going to be stored. | In this variable user can enter either yes or no to indicate whether the prediction is right or wrong. | In this variable user will enter the correct label as a feedback inorder to retrain the model. | In this variable all predictions after feedback loop are going to be stored. |

sentiment_analysis_corpus.csv

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sentiment_analysis_train.csv

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