Splunk Machine Learning Toolkit: How to make DBSCAN work with partial fit?

[rosho]

Hi,
I am working on a Forecasting problem. This is my procedure:

a) Standard scaler (supports partial fit)
b) Detect outliers using DBSCAN (does not support partial fit)
c) Forecast with Kalman filter (not sure of this???) or MLP (supports partial fit)

So, I would like to know if this procedure is possible to use "partial fit" (incremental learning)?
Or do all algorithms have to support partial fit?

Thank you.

[grana_splunk]

Can you add more detail on your usecase? Also, I would recommend you to use StateSpace algorithm for forecasting as it supports partial fit. Check the documentation here: https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#StateSpaceForecast

[rosho]

Hi @grana_splunk

I am predicting the number of logins. My dataset has the number of logins by hour (1 month).

I use a) and b) to clean the data (removing or transforming outliers).
With c) I forecast

a) Standard scaler
b) Detect outliers using DBSCAN
c) Forecast with Kalman filter or MLP