diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/pyspark/ml/regression.py | 7 | ||||
| -rw-r--r-- | python/pyspark/ml/tuning.py | 2 |
2 files changed, 5 insertions, 4 deletions
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py index da74ab5070..8e76070e9a 100644 --- a/python/pyspark/ml/regression.py +++ b/python/pyspark/ml/regression.py @@ -561,7 +561,7 @@ class TreeRegressorParams(Params): impurity = Param(Params._dummy(), "impurity", "Criterion used for information gain calculation (case-insensitive). " + "Supported options: " + - ", ".join(supportedImpurities)) + ", ".join(supportedImpurities), typeConverter=TypeConverters.toString) def __init__(self): super(TreeRegressorParams, self).__init__() @@ -1261,11 +1261,12 @@ class GeneralizedLinearRegression(JavaEstimator, HasLabelCol, HasFeaturesCol, Ha family = Param(Params._dummy(), "family", "The name of family which is a description of " + "the error distribution to be used in the model. Supported options: " + - "gaussian(default), binomial, poisson and gamma.") + "gaussian(default), binomial, poisson and gamma.", + typeConverter=TypeConverters.toString) link = Param(Params._dummy(), "link", "The name of link function which provides the " + "relationship between the linear predictor and the mean of the distribution " + "function. Supported options: identity, log, inverse, logit, probit, cloglog " + - "and sqrt.") + "and sqrt.", typeConverter=TypeConverters.toString) @keyword_only def __init__(self, labelCol="label", featuresCol="features", predictionCol="prediction", diff --git a/python/pyspark/ml/tuning.py b/python/pyspark/ml/tuning.py index ef14da488e..b16628bc70 100644 --- a/python/pyspark/ml/tuning.py +++ b/python/pyspark/ml/tuning.py @@ -448,7 +448,7 @@ class TrainValidationSplit(Estimator, ValidatorParams, MLReadable, MLWritable): """ trainRatio = Param(Params._dummy(), "trainRatio", "Param for ratio between train and\ - validation data. Must be between 0 and 1.") + validation data. Must be between 0 and 1.", typeConverter=TypeConverters.toFloat) @keyword_only def __init__(self, estimator=None, estimatorParamMaps=None, evaluator=None, trainRatio=0.75, |