The project is mostly concerned with feature engineering. To help the model grasp the data better, created additional features based on the disaster tweets. In the included notebook, each and every step is described in depth. In the supplied data set, I also dealt with the class imbalance. Final results: F1 Score 0.7031431897555296 Precision Score 0.6771300448430493 Recall Score 0.7312348668280871 ROC AUC Score 0.8269285564661661 Average Precision Score 0.5439537630737555
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The project is mostly concerned with feature engineering. To help the model grasp the data better, created additional features based on the disaster tweets. In the included notebook, each and every step is described in depth. In the supplied data set, I also dealt with the class imbalance. Final results: F1 Score 0.7031431897555296 Precision Sco…
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VaradrajPoojari/Disaster_tweet
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The project is mostly concerned with feature engineering. To help the model grasp the data better, created additional features based on the disaster tweets. In the included notebook, each and every step is described in depth. In the supplied data set, I also dealt with the class imbalance. Final results: F1 Score 0.7031431897555296 Precision Sco…
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