Improving predictive accuracy involves several strategies:
Enhanced Data Collection: Collecting more comprehensive and high-quality data. Model Validation: Using techniques like cross-validation to ensure the model performs well on unseen data. Algorithm Selection: Choosing appropriate algorithms that fit the nature of the data and the prediction problem. Feature Selection: Identifying and using the most relevant variables for the prediction.
