How can I improve my anomaly detection models?

How can I improve my anomaly detection models?

To improve your anomaly detection models, consider using more diverse training data, feature engineering, and tuning hyperparameters.

What types of features should I focus on?

Focus on features that capture the underlying patterns of your data, such as temporal features, categorical variables, and interaction terms.

Are there specific algorithms that work better for anomaly detection?

Yes, algorithms like Isolation Forest, One-Class SVM, and Autoencoders are popular for anomaly detection tasks.

How can I evaluate the performance of my model?

You can evaluate your model using metrics like precision, recall, F1-score, and ROC-AUC, especially on a labeled dataset.