I would like to do outlier or anomaly detection on the disk free space data. Sample dataset as below (I don't have any label dataset):
date free_space (GB) 2019-05-15 09:00:00 102.65 2019-05-15 09:05:00 102.69 2019-05-15 09:10:00 103.11 2019-05-15 09:15:00 102.58 2019-05-15 09:20:00 102.55
I would like to detect whether the new value of disk space is an outlier or not. There are several outlier analysis methods (ref link):
- Box plot analysis
- Based on Z score
- IQR based analysis (this is similar to box plot analysis)
Above methods are more statistical approach to detect outlier. There are several ways using an unsupervised machine learning algorithm to detect outlier (ref link). For example,
- Markov Chain
- Isolation Forest etc.
Which method is suitable for the above dataset? Should I implement unsupervised based machine learning algorithm or statistical approach?