Hi,

I was wondering if it would be possible to fit only the intercept on a LinearRegression instance by providing a known coefficient?

Here is some background information: we have a problem where linear regression is well suited as a predictor. However, the model requires continuous adoption. During an initial training, the coefficient and the intercept of the linear model are determined from a given set of training data. Later, this model requires adoption during which the intercept has to be adopted to a new set of training data (the coefficient, in other words the slope, remains the same as obtained from the initial model).

I had a look on the Java API for LinearRegression and could not find a way how to only fit the intercept and set initial parameters for a fit. Am I missing something? Is there a way how to to do this with the LinearRegression class in Sparks' ML package or do I have to use a different approach?

Thanks in advance.

regards

Eugen