Overfitting to Training Data
Challenge: Models overfit to specific training data, hindering generalization.
Solution: Utilize techniques like cross-validation, regularization, or early stopping to prevent overfitting. Employ data augmentation to increase the diversity of training samples.
Feature Selection and Extraction Challenges
Challenge: Difficulty in selecting and extracting meaningful features for effective modeling.
Solution: Implement feature engineering techniques like dimensionality reduction, feature scaling, and filter methods. Leverage domain knowledge to identify relevant features and utilize feature importance metrics to prioritize their selection.
