I am working on an unsupervised anomaly detection task on time series data using an isolation forest algorithm.
I am developing it in Python, more in detail using scikit-learn
.
I found a lot of examples on this, but what is not very clear, is how to set the contamination parameter during the instantiation of IsolationForest.
Looking at the documentation, contamination is
the amount of contamination of the data set, i.e. the proportion of outliers in the data set.
Should I use some statistical techniques to identify this percentage?