How can I improve the accuracy of my anomaly detection model?

How can I improve the accuracy of my anomaly detection model?

To improve accuracy, consider using more diverse training data, feature engineering, and advanced algorithms.

What specific algorithms do you recommend for anomaly detection?

Some popular algorithms include Isolation Forest, One-Class SVM, and Autoencoders. It depends on your data.

How important is feature selection in this process?

Feature selection is crucial as it helps in reducing noise and improving model performance.

Can I use ensemble methods to enhance my model?

Yes, ensemble methods can combine multiple models to improve accuracy and robustness.

What metrics should I use to evaluate my model's performance?

Common metrics include precision, recall, F1-score, and ROC-AUC, depending on your specific use case.