Anomaly detection with OPTICS


Hi all,

I have a workflow that trains a DBSCAN model using OPTICS (Cluster Compute & Cluster Assigner) in order to detect any anomaly on data. This model is trained using almost all my historical data (aggregated by day, 729 days in total) but last month. Now, I’m trying to use that model (generated by OPTICS cluster Compute) and data from yesterday to evaluate if there is some anomaly. But I don’t know how I can do it.

After loading the model with a “Model Reader” node, OPTICS Cluster gives me an error related with different sizes (The length of the model doesn’t correspond to the given data. (1!=729)). Obviously I don’t want to re-train the model, only use it to cluster yesterday data.

Any suggestion?

Thanks in advance.