R/models.R
Simple Co-Occurrence based tabulation of X vs Y, where X and Y are two Vecs in a given dataset. Uses histogram of given resolution in X and Y. Handles numerical/categorical data and missing values. Supports observation weights.
h2o.tabulate(data, x, y, weights_column = NULL, nbins_x = 50, nbins_y = 50)
data | An H2OFrame object. |
---|---|
x | predictor column |
y | response column |
weights_column | (optional) observation weights column |
nbins_x | number of bins for predictor column |
nbins_y | number of bins for response column |
Returns two TwoDimTables of 3 columns each count_table: X Y counts response_table: X meanY counts
# NOT RUN { library(h2o) h2o.init() df <- as.h2o(iris) tab <- h2o.tabulate(data = df, x = "Sepal.Length", y = "Petal.Width", weights_column = NULL, nbins_x = 10, nbins_y = 10) plot(tab) # }