H2O Generalized Low Rank Models (Missing Value Impute)

Learner

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 Frame with input data.

Output Ports

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

Find here

KNIME Labs > H2O Machine Learning > Models > Generalized Low Rank Models

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