H2O Generalized Low Rank Models (Missing Value Impute)

Apply a Generalized Low Rank Model (GLRM) using H2O to reconstruct missing values or identify important features in a dataset. Note that if the input data contains no missing values, the reconstructed data returned by this node will be the same as the input data.

Input ports

1. Type: H2O Frame
   H2O input data frame.
   H2O Frame with input data.

Output ports

1. Type: H2O Frame
   H2O GLRM reconstructed data.
   H2O Frame with the reconstructed input data.
2. Type: H2O Frame
   H2O GLRM X matrix.
   H2O Frame with the GLRM X matrix. The X matrix contains k principal components of the input data.