The “h2o.cor” Function in R

• Package: h2o

• Purpose: To compute the correlation matrix for numeric columns of an H2O data frame.

• General Class: Data Analysis

• Required Argument(s):

• x: H2OFrame. The H2O data frame for which the correlation matrix is computed.

• Notable Optional Arguments:

• y: H2OFrame. An optional second H2O data frame to be correlated with the columns of the first data frame.

• na.rm: Logical. Whether to remove NA values from the computation. The default is FALSE.

• method: Character. The correlation method to be used. Options include "pearson", "spearman", and "kendall". The default is "pearson".

• Example (with Explanation):

• # Load necessary package
  library(h2o)
  
  # Initialize H2O
  h2o.init()
  
  # Load a sample dataset
  data1 <- data2 <- h2o.importFile("https://s3.amazonaws.com/h2o-public-test-data/smalldata/iris/iris_wheader.csv")
  
  # Compute correlation matrix
  cor_matrix <- h2o.cor(x = data1, y = data2, na.rm = TRUE, method = "spearman")
  
  # View the correlation matrix
  print(cor_matrix)

• In this example, the h2o.cor function from the h2o package is used to compute the correlation matrix between the numeric columns of two H2O data frames (data1 and data2). NA values are removed (na.rm = TRUE), and the Spearman correlation method is used (method = "spearman"). The resulting correlation matrix is then printed to the console.