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Implemented N.L.P. applications with random forest classifier, CatBoostclassifier, and XGBoost classifier models, with and without hyperparameter tuning, to predict whether the news headlines given as input will have a negative or positive impact on the stocks based on the closing index.

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anshulsingh8101/Stock_prediction_from_news_headlines-NLP

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Stock_news_headlines

First Model --------------------------------------------> Random Forest without any Hyperparameter tuning



Second Model --------------------------------------------> Random Forest with Hyperparameter tuning



Third Model --------------------------------------------> Xg_boost_model Without any hypertuning



Fourth Model --------------------------------------------> Xg_boost_model with hypertuning



Fifth Model --------------------------------------------> CATBOOST



Code for making the below plotly visualization ------------------------------------------------------------------------------/



Accuracy Score -------------------------------------------------------------------------------------------------------------/



True Positive and false negative values using plotly visualization ---------------------------------------------------------/

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Implemented N.L.P. applications with random forest classifier, CatBoostclassifier, and XGBoost classifier models, with and without hyperparameter tuning, to predict whether the news headlines given as input will have a negative or positive impact on the stocks based on the closing index.

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