Skip to content

[Minor] [ML] [PySpark] Fix omissive params which should use TypeConverter #12529

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
yanboliang wants to merge 1 commit into from
Closed

[Minor] [ML] [PySpark] Fix omissive params which should use TypeConverter #12529

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
7 changes: 4 additions & 3 deletions python/pyspark/ml/regression.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -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__()
Expand Down Expand Up @@ -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",
Expand Down
2 changes: 1 addition & 1 deletion python/pyspark/ml/tuning.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -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,
Expand Down