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[SPARK-7474] [MLLIB] update ParamGridBuilder doctest

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Multiline commands are properly handled in this PR. oefirouz

![screen shot 2015-05-07 at 10 53 25 pm](https://cloud.githubusercontent.com/assets/829644/7531290/02ad2fd4-f50c-11e4-8c04-e58d1a61ad69.png)

Author: Xiangrui Meng <meng@databricks.com>

Closes #6001 from mengxr/SPARK-7474 and squashes the following commits:

b94b11d [Xiangrui Meng] update ParamGridBuilder doctest
This commit is contained in:
Xiangrui Meng 2015-05-08 11:16:04 -07:00
parent f5ff4a84c4
commit 65afd3ce8b
1 changed files with 13 additions and 15 deletions
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28
python/pyspark/ml/tuning.py
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@ -27,24 +27,22 @@ __all__ = ['ParamGridBuilder', 'CrossValidator', 'CrossValidatorModel']
class ParamGridBuilder(object):
"""
r"""
Builder for a param grid used in grid search-based model selection.
>>> from classification import LogisticRegression
>>> from pyspark.ml.classification import LogisticRegression
>>> lr = LogisticRegression()
>>> output = ParamGridBuilder().baseOn({lr.labelCol: 'l'}) \
.baseOn([lr.predictionCol, 'p']) \
.addGrid(lr.regParam, [1.0, 2.0, 3.0]) \
.addGrid(lr.maxIter, [1, 5]) \
.addGrid(lr.featuresCol, ['f']) \
.build()
>>> expected = [ \
{lr.regParam: 1.0, lr.featuresCol: 'f', lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, \
{lr.regParam: 2.0, lr.featuresCol: 'f', lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, \
{lr.regParam: 3.0, lr.featuresCol: 'f', lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, \
{lr.regParam: 1.0, lr.featuresCol: 'f', lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}, \
{lr.regParam: 2.0, lr.featuresCol: 'f', lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}, \
{lr.regParam: 3.0, lr.featuresCol: 'f', lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}]
>>> output = ParamGridBuilder() \
... .baseOn({lr.labelCol: 'l'}) \
... .baseOn([lr.predictionCol, 'p']) \
... .addGrid(lr.regParam, [1.0, 2.0]) \
... .addGrid(lr.maxIter, [1, 5]) \
... .build()
>>> expected = [
... {lr.regParam: 1.0, lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'},
... {lr.regParam: 2.0, lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'},
... {lr.regParam: 1.0, lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'},
... {lr.regParam: 2.0, lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}]
>>> len(output) == len(expected)
True
>>> all([m in expected for m in output])