In online machine learning algorithm linear regression stochastic gradient , when new training data comes do we have to mix it with prevoius data?

Question

Suppose I have 1 billion data set points, with which we already trained our machine learning model and obtained our parameters / weights . Now i receive another 100 data set points , how i train this new data set ? Deviating from linear regression , how do we train new examples of spam/not spam in spam filtering , if we had already trained let say 2 billion mails ?

blazs blazs · Accepted Answer · 2016-03-16T13:07:27

It seems to me that you should use a different algorithm (i.e. an online algorithm).

I've never tried this in practice, but here's a paper from NIPS (a well-respected ML conference) that you may find useful: Online Linear Regression and Its Application to Model-Based Reinforcement Learning. (This same algorithm was suggested in an answer to a similar question on Cross Validated.)

In online machine learning algorithm linear regression stochastic gradient , when new training data comes do we have to mix it with prevoius data?

1 Answers