.. _parameters_H2OGridSearch:

Parameters of H2OGridSearch
---------------------------

Affected Class
##############

- ``ai.h2o.sparkling.ml.algos.H2OGridSearch``

Parameters
##########

- *Each parameter has also a corresponding getter and setter method.*
  *(E.g.:* ``label`` *->* ``getLabel()`` *,* ``setLabel(...)`` *)*

algo
  Specifies the algorithm for grid search

  *Scala default value:* ``null`` *; Python default value:* ``None``
  

hyperParameters
  Hyper Parameters

  *Scala default value:* ``Map()`` *; Python default value:* ``{}``
  

parallelism
  Level of model-building parallelism, the possible values are:

  - 0 -> H2O selects parallelism level based on cluster configuration, such as number of cores

  - 1 -> Sequential model building, no parallelism

  - n>1 -> n models will be built in parallel if possible

  *Default value:* ``1``
  

selectBestModelBy
  Select best model by specific metric.If this value is not specified that the first model os taken.

  *Default value:* ``"AUTO"``
  

maxModels
  Maximum number of models to build (optional).

  *Default value:* ``0``
  

maxRuntimeSecs
  Maximum time to spend building models (optional).

  *Default value:* ``0.0``
  

seed
  Seed for random number generator; set to a value other than -1 for reproducibility.

  *Scala default value:* ``-1L`` *; Python default value:* ``-1``
  

stoppingMetric
  Metric to use for early stopping (AUTO: logloss for classification, deviance for regression). Possible values are ``"AUTO"``, ``"deviance"``, ``"logloss"``, ``"MSE"``, ``"RMSE"``, ``"MAE"``, ``"RMSLE"``, ``"AUC"``, ``"AUCPR"``, ``"lift_top_group"``, ``"misclassification"``, ``"mean_per_class_error"``, ``"anomaly_score"``, ``"custom"``, ``"custom_increasing"``.

  *Default value:* ``"AUTO"``
  

stoppingRounds
  Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable).

  *Default value:* ``0``
  

stoppingTolerance
  Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much).

  *Default value:* ``0.001``
  

strategy
  Hyperparameter space search strategy. Possible values are ``"Unknown"``, ``"Cartesian"``, ``"RandomDiscrete"``, ``"Sequential"``.

  *Default value:* ``"Cartesian"``