Model

For detailed information on the specifications of each model, refer to Data Science in H2O. Tutorials for each algorithm and model specifications through R are available in the Tutorial Documentation.

Specify a model by making a selection from the list of algorithms at the top of the Inspect page when data are parsed or by selecting the appropriate model from the drop-down Model menu.

Each model requires a .hex key that is associated with a data set. The entry fields use auto-complete, so you can often begin typing the name of the original data source to select the appropriate .hex key from the listed options. To locate .hex keys for data sets, select View All from the drop-down Data menu. To locate .hex keys for all H2O actions, select Jobs from the drop-down Admin menu.

If a large data set is used in the training and testing of a model, H2O’s capabilities are constrained by the amount of memory available on the machine. To utilize H2O’s full capability, the amount of memory available should be about four times the file size of the data set, but not more than the machine’s total available memory. For instructions on how to change the amount of memory allocated to H2O, see the “Important Notes” section in Getting Started From a Downloaded Zip File. Advanced users should run H2O on a cloud computing resource or server.

Grid Search Models

GLM and GBM both offer Grid Search Models. To use this option in GLM, select GLM Grid Search from the drop-down Model menu.

Each grid search modeling option allows users to generate multiple models simultaneously and compare model criteria directly, rather than building models separately one at a time. Specify multiple model configurations by entering different values of tuning parameters separated by commas. For example, to specify three different values of lambda (a regularization parameter in GLM Grid search), users might enter: .001, .05, .1.

When multiple values are specified for many tuning parameters, grid search returns one model for each unique combination. For example, in GBM, if users specify Ntrees as 50, 100, 200 and specify learning rates of 0.01 and 0.05, six models are returned.

The grid search results display in a table, showing the combination of tuning parameters used for each model and basic model evaluation information, as well as a link to each model. To access the details of each model, click the model links in the table.