{
  "org.apache.spark.ml.classification.DecisionTreeClassifier.label": "Random Forest Classifier",
  "org.apache.spark.ml.classification.DecisionTreeClassifier.desc": "Fitted Random Forest Classification Model",
  "inputFieldList.label": "Input columns",
  "inputFieldList.desc": "Select one or more input columns",
  "targetField.label": "Target column",
  "targetField.desc": "Select a target column",
  "checkpointInterval.label": "Checkpoint Interval",
  "checkpointInterval.desc": "Set checkpoint interval (>= 1) or disable checkpoint (-1). Ex) 10 means that the cache will get checkpointed every 10 iterations",
  "impurity.label": "Impurity",
  "impurity.desc": "Criterion used for information gain calculation (case-insensitive). Supported: \"entropy\" and \"gini\"",
  "lossType.label": "Loss Type",
  "lossType.desc": "Loss function which GBT tries to minimize",
  "maxBins.label": "Maximum number of bins",
  "maxBins.desc": "Maximum number of bins used for discretizing continuous features and for choosing how to split on features at each node. More bins give higher granularity. Must be >= 2 and >= number of categories in any categorical feature",
  "maxDepth.label": "Maximum depth of the tree",
  "maxDepth.desc": "Maximum depth of the tree (>= 0). Ex) depth 0 means 1 leaf node; depth 1 means 1 internal node + 2 leaf nodes",
  "maxIter.label": "Maximum iterations for convergence",
  "maxIter.desc": "Maximum iterations for convergence (>= 0)",
  "minInfoGain.label": "Minimum information gain",
  "minInfoGain.desc": "Minimum information gain for a split to be considered at a tree node",
  "minInstancesPerNode.label": "Minimum instances per node",
  "minInstancesPerNode.desc": "Minimum number of instances each child must have after split. If a split causes the left or right child to have fewer than minInstancesPerNode, the split will be discarded as invalid (>= 1)",
  "seed.label": "Seed",
  "seed.desc": "Random seed",
  "stepSize.label": "Step size",
  "stepSize.desc": "Step size to be used for each iteration of optimization",
  "subsamplingRate.label": "Subsampling Rate",
  "subsamplingRate.desc": "Fraction of the training data used for learning each decision tree (> 0 and <= 1)",
  "fields_settings.label": "Fields",
  "input_field_list_not_empty": "Select one or more input columns",
  "target_field_not_empty": "Select a target field",
  "checkpoint_interval_not_valid": "The checkpoint interval value must either be >= 1 or -1 to disable",
  "max_bins_not_valid": "Max bins must be >= 2 and >= number of categories in any categorical feature",
  "max_depth_not_valid": "The max depth parameter must be greater than or equal to zero",
  "max_iter_not_valid": "The max iterations parameter must be greater than or equal to zero",
  "min_instances_per_node_not_valid": "The minimum instances per node value must be >= 1",
  "subsampling_rate_not_valid": "The subsampling rate value must be > 0 and <= 1"
}