Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/10598#discussion_r51642291
--- Diff: python/pyspark/mllib/classification.py ---
@@ -272,37 +275,42 @@ def train(cls, data, iterations=100, step=1.0,
miniBatchFraction=1.0,
"""
Train a logistic regression model on the given data.
- :param data: The training data, an RDD of
- LabeledPoint.
- :param iterations: The number of iterations
- (default: 100).
- :param step: The step parameter used in SGD
- (default: 1.0).
- :param miniBatchFraction: Fraction of data to be used for each
- SGD iteration (default: 1.0).
- :param initialWeights: The initial weights (default: None).
- :param regParam: The regularizer parameter
- (default: 0.01).
- :param regType: The type of regularizer used for
- training our model.
-
- :Allowed values:
- - "l1" for using L1 regularization
- - "l2" for using L2 regularization
- - None for no regularization
-
- (default: "l2")
-
- :param intercept: Boolean parameter which indicates the
- use or not of the augmented
representation
- for training data (i.e. whether bias
- features are activated or not,
- default: False).
- :param validateData: Boolean parameter which indicates if
- the algorithm should validate data
- before training. (default: True)
- :param convergenceTol: A condition which decides iteration
termination.
- (default: 0.001)
+ :param data:
+ The training data, an RDD of LabeledPoint.
+ :param iterations:
+ The number of iterations.
+ (default: 100)
+ :param step:
+ The step parameter used in SGD.
+ (default: 1.0)
+ :param miniBatchFraction:
+ Fraction of data to be used for each SGD iteration.
+ (default: 1.0)
+ :param initialWeights:
+ The initial weights.
+ (default: None)
+ :param regParam:
+ The regularizer parameter.
+ (default: 0.01)
+ :param regType:
+ The type of regularizer used for training our model.
+ :Allowed values:
+ - "l1" for using L1 regularization
+ - "l2" for using L2 regularization
+ - None for no regularization
+ (default: "l2")
--- End diff --
It looks like we have a problem with the formatting of this param. If we
want the html to look the same and get rid of any warnings, then I think it has
to be written like this
```
:param regType:
The type of regularizer used for training our model.
:Allowed values:
- "l1" for using L1 regularization
- "l2" for using L2 regularization
- None for no regularization
(default: "l2")
```
which, I think, looks ugly in the code and not even that great in the html.
Alternatively, we could rewrite it inline similar to how some other params
have it, like this
```
:param regType:
The type of regularizer used for training our model.
Allowed values: "l1" for using L1 regularization;
"l2" for using L2 regularization; None for no
regularization.
(default: "l2")
```
Not perfect, but both code and html look decent, imho.
@mengxr , would you be ok with the second inline format?
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