class_docstr: RuleFit
  
  Builds a RuleFit on a parsed dataset, for regression or 
  classification. 
class_docstr_tok: ["RuleFit","Builds","a","RuleFit","on","a","parsed","dataset",",","for","regression","or","classification","."]
docstr: Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the
  dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative
  weights are not allowed. Note: Weights are per-row observation weights and do not increase the size of the data
  frame. This is typically the number of times a row is repeated, but non-integer values are supported as well.
  During training, rows with higher weights matter more, due to the larger loss function pre-factor. If you set
  weight = 0 for a row, the returned prediction frame at that row is zero and this is incorrect. To get an
  accurate prediction, remove all rows with weight == 0.
  
  Type: ``str``.
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code: def weights_column(self):
      """
      Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the
      dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative
      weights are not allowed. Note: Weights are per-row observation weights and do not increase the size of the data
      frame. This is typically the number of times a row is repeated, but non-integer values are supported as well.
      During training, rows with higher weights matter more, due to the larger loss function pre-factor. If you set
      weight = 0 for a row, the returned prediction frame at that row is zero and this is incorrect. To get an
      accurate prediction, remove all rows with weight == 0.
  
      Type: ``str``.
      """
      return self._parms.get("weights_column")
  
imports: from h2o.utils.metaclass import deprecated_params, deprecated_property
  import h2o
  from h2o.estimators.estimator_base import H2OEstimator
  from h2o.exceptions import H2OValueError
  from h2o.frame import H2OFrame
  from h2o.utils.typechecks import assert_is_type, Enum, numeric
label_desc: Use image node_id 22 for calling the H2ORuleFitEstimator obj's underlying member method code with example usage: obj.weights_column() and returns: self