Handling Imbalanced Data Classification Problems

Explore the complexities of handling imbalanced data classification problems in this 2-hour project-based course. Gain insights into understanding the business problem, dataset evaluation, and data resampling techniques like SMOTE, undersampling, and oversampling. With a focus on North America, you will learn to implement the ROC curve and adjust probability thresholds to enhance model performance.

• Understand the business problem and dataset to choose the best evaluation metric
• Create imbalanced data classification model using SMOTE data resampling technique
• Compute the ROC curve and use it to adjust the probability threshold