diff options
Diffstat (limited to 'python/pyspark/ml/param/shared.py')
| -rw-r--r-- | python/pyspark/ml/param/shared.py | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/python/pyspark/ml/param/shared.py b/python/pyspark/ml/param/shared.py index 9ed63e48ae..c5ccf81540 100644 --- a/python/pyspark/ml/param/shared.py +++ b/python/pyspark/ml/param/shared.py @@ -328,10 +328,10 @@ class HasSeed(Params): class HasTol(Params): """ - Mixin for param tol: the convergence tolerance for iterative algorithms. + Mixin for param tol: the convergence tolerance for iterative algorithms (>= 0). """ - tol = Param(Params._dummy(), "tol", "the convergence tolerance for iterative algorithms.", typeConverter=TypeConverters.toFloat) + tol = Param(Params._dummy(), "tol", "the convergence tolerance for iterative algorithms (>= 0).", typeConverter=TypeConverters.toFloat) def __init__(self): super(HasTol, self).__init__() @@ -351,10 +351,10 @@ class HasTol(Params): class HasStepSize(Params): """ - Mixin for param stepSize: Step size to be used for each iteration of optimization. + Mixin for param stepSize: Step size to be used for each iteration of optimization (>= 0). """ - stepSize = Param(Params._dummy(), "stepSize", "Step size to be used for each iteration of optimization.", typeConverter=TypeConverters.toFloat) + stepSize = Param(Params._dummy(), "stepSize", "Step size to be used for each iteration of optimization (>= 0).", typeConverter=TypeConverters.toFloat) def __init__(self): super(HasStepSize, self).__init__() @@ -374,10 +374,10 @@ class HasStepSize(Params): class HasHandleInvalid(Params): """ - Mixin for param handleInvalid: how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an errror). More options may be added later. + Mixin for param handleInvalid: how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an error). More options may be added later. """ - handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an errror). More options may be added later.", typeConverter=TypeConverters.toString) + handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an error). More options may be added later.", typeConverter=TypeConverters.toString) def __init__(self): super(HasHandleInvalid, self).__init__() |