I have a workflow that trains a DBSCAN model using OPTICS (Cluster Compute & Cluster Assigner) in order to detect anomalies in data. This model is trained using almost all my historical data (data is 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 yesterday there was 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.
Thanks in advance.