How to get archetypes from a GLRM model in H2O


GLRM is a new machine learning approach for reconstructing missing values and identifying important features in heterogeneous data.

Learn more about GLRM Models in H2O:

The following code snippet helps users to use R/python interface to get archetypes from a GLRM which are not available from FLOW:

> h2o.init()
> cancar = h2o.importFile(" data/smalldata/glrm_test/cancar.csv")
> cancar.splits = h2o.splitFrame(cancar, ratios = .5, seed = 1234)
> model1 <- h2o.glrm(training_frame = cancar.splits[[1]],k=4)
> fitY <- model1@model$archetypes
> model2 <- h2o.glrm(training_frame = cancar.splits[[2]], init = "User", user_y = fitY)



Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s