Localized Flood Detection With Minimal Labeled Social Media Data Using Transfer Learning
Table 3: Evaluation Metrics for Queensland Flood Data
['[BOLD] Labeled Data% Target', '[BOLD] Class Label', '[BOLD] Precision', '[BOLD] Recall', '[BOLD] F1-score', '[BOLD] Accuracy']
Here, Our focus is localized flood detection thus we are not merging multiple datasets, we will leave the combination for our future work and staying with one Queensland flood data and explore that in details. This model is very efficient and effective when we have a time-sensitive application and instead of training a model from scratch with huge data we can use the pre-trained model and successfully applies to the target domain application. There is generally a direct relation which says the more training data is the better but here increased labeled data the accuracy did not contribute significantly towards the accuracy improvement.