What are the different methods for anomaly detection?

What are the different methods for anomaly detection?

There are several methods for anomaly detection, including statistical methods, machine learning techniques, and deep learning approaches. Would you like a detailed comparison?

Yes, please compare them in terms of accuracy and complexity.

Statistical methods are often simpler and faster but may lack accuracy in complex datasets. Machine learning methods, like SVM or decision trees, offer better accuracy but require more data and tuning. Deep learning methods can achieve high accuracy but are computationally intensive and require large datasets.

Which method would you recommend for a small dataset?

For a small dataset, I would recommend starting with statistical methods or simpler machine learning techniques, as they are less prone to overfitting.

Are there any specific algorithms you suggest?

Yes, for statistical methods, you can use Z-score or IQR. For machine learning, consider using Isolation Forest or k-Nearest Neighbors.