Reconstruct the training data and impute missing values from the H2O GLRM model by computing the matrix product of X and Y, and transforming back to the original feature space by minimizing each column's loss function.
object: An H2ODimReductionModel object that represents the model to be used for reconstruction.
data: An H2OFrame object representing the training data for the H2O GLRM model. Used to set the domain of each column in the reconstructed frame.
reverse_transform: (Optional) A logical value indicating whether to reverse the transformation from model-building by re-scaling columns and adding back the offset to each column of the reconstructed frame.
Returns
Returns an H2OFrame object containing the approximate reconstruction of the training data;
Examples
## Not run:library(h2o)h2o.init()iris_hf <- as.h2o(iris)iris_glrm <- h2o.glrm(training_frame = iris_hf, k =4, transform ="STANDARDIZE", loss ="Quadratic", multi_loss ="Categorical", max_iterations =1000)iris_rec <- h2o.reconstruct(iris_glrm, iris_hf, reverse_transform =TRUE)head(iris_rec)## End(Not run)