aboutsummaryrefslogtreecommitdiff
path: root/python/pyspark/ml/evaluation.py
Commit message (Collapse)AuthorAgeFilesLines
* [SPARK-14971][ML][PYSPARK] PySpark ML Params setter code clean upYanbo Liang2016-05-031-6/+3
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? PySpark ML Params setter code clean up. For examples, ```setInputCol``` can be simplified from ``` self._set(inputCol=value) return self ``` to: ``` return self._set(inputCol=value) ``` This is a pretty big sweeps, and we cleaned wherever possible. ## How was this patch tested? Exist unit tests. Author: Yanbo Liang <ybliang8@gmail.com> Closes #12749 from yanboliang/spark-14971.
* [SPARK-14555] First cut of Python API for Structured StreamingBurak Yavuz2016-04-201-2/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch provides a first cut of python APIs for structured streaming. This PR provides the new classes: - ContinuousQuery - Trigger - ProcessingTime in pyspark under `pyspark.sql.streaming`. In addition, it contains the new methods added under: - `DataFrameWriter` a) `startStream` b) `trigger` c) `queryName` - `DataFrameReader` a) `stream` - `DataFrame` a) `isStreaming` This PR doesn't contain all methods exposed for `ContinuousQuery`, for example: - `exception` - `sourceStatuses` - `sinkStatus` They may be added in a follow up. This PR also contains some very minor doc fixes in the Scala side. ## How was this patch tested? Python doc tests TODO: - [ ] verify Python docs look good Author: Burak Yavuz <brkyvz@gmail.com> Author: Burak Yavuz <burak@databricks.com> Closes #12320 from brkyvz/stream-python.
* [SPARK-14104][PYSPARK][ML] All Python param setters should use the `_set` methodsethah2016-04-151-7/+10
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Param setters in python previously accessed the _paramMap directly to update values. The `_set` method now implements type checking, so it should be used to update all parameters. This PR eliminates all direct accesses to `_paramMap` besides the one in the `_set` method to ensure type checking happens. Additional changes: * [SPARK-13068](https://github.com/apache/spark/pull/11663) missed adding type converters in evaluation.py so those are done here * An incorrect `toBoolean` type converter was used for StringIndexer `handleInvalid` param in previous PR. This is fixed here. ## How was this patch tested? Existing unit tests verify that parameters are still set properly. No new functionality is actually added in this PR. Author: sethah <seth.hendrickson16@gmail.com> Closes #11939 from sethah/SPARK-14104.
* [SPARK-14472][PYSPARK][ML] Cleanup ML JavaWrapper and related class hierarchyBryan Cutler2016-04-131-2/+2
| | | | | | | | | | Currently, JavaWrapper is only a wrapper class for pipeline classes that have Params and JavaCallable is a separate mixin that provides methods to make Java calls. This change simplifies the class structure and to define the Java wrapper in a plain base class along with methods to make Java calls. Also, renames Java wrapper classes to better reflect their purpose. Ran existing Python ml tests and generated documentation to test this change. Author: Bryan Cutler <cutlerb@gmail.com> Closes #12304 from BryanCutler/pyspark-cleanup-JavaWrapper-SPARK-14472.
* [SPARK-10509][PYSPARK] Reduce excessive param boiler plate codeHolden Karau2016-01-261-12/+0
| | | | | | | | The current python ml params require cut-and-pasting the param setup and description between the class & ```__init__``` methods. Remove this possible case of errors & simplify use of custom params by adding a ```_copy_new_parent``` method to param so as to avoid cut and pasting (and cut and pasting at different indentation levels urgh). Author: Holden Karau <holden@us.ibm.com> Closes #10216 from holdenk/SPARK-10509-excessive-param-boiler-plate-code.
* [SPARK-9716][ML] BinaryClassificationEvaluator should accept Double ↵BenFradet2016-01-191-2/+3
| | | | | | | | | | prediction column This PR aims to allow the prediction column of `BinaryClassificationEvaluator` to be of double type. Author: BenFradet <benjamin.fradet@gmail.com> Closes #10472 from BenFradet/SPARK-9716.
* [SPARK-10286][ML][PYSPARK][DOCS] Add @since annotation to pyspark.ml.param ↵lihao2015-11-021-0/+20
| | | | | | | | and pyspark.ml.* Author: lihao <lihaowhu@gmail.com> Closes #9275 from lidinghao/SPARK-10286.
* [SPARK-10188] [PYSPARK] Pyspark CrossValidator with RMSE selects incorrect modelnoelsmith2015-08-271-0/+12
| | | | | | | | | | | | | * Added isLargerBetter() method to Pyspark Evaluator to match the Scala version. * JavaEvaluator delegates isLargerBetter() to underlying Scala object. * Added check for isLargerBetter() in CrossValidator to determine whether to use argmin or argmax. * Added test cases for where smaller is better (RMSE) and larger is better (R-Squared). (This contribution is my original work and that I license the work to the project under Sparks' open source license) Author: noelsmith <mail@noelsmith.com> Closes #8399 from noel-smith/pyspark-rmse-xval-fix.
* [SPARK-10097] Adds `shouldMaximize` flag to `ml.evaluation.Evaluator`Feynman Liang2015-08-191-2/+2
| | | | | | | | | | | | | Previously, users of evaluator (`CrossValidator` and `TrainValidationSplit`) would only maximize the metric in evaluator, leading to a hacky solution which negated metrics to be minimized and caused erroneous negative values to be reported to the user. This PR adds a `isLargerBetter` attribute to the `Evaluator` base class, instructing users of `Evaluator` on whether the chosen metric should be maximized or minimized. CC jkbradley Author: Feynman Liang <fliang@databricks.com> Author: Joseph K. Bradley <joseph@databricks.com> Closes #8290 from feynmanliang/SPARK-10097.
* [SPARK-9828] [PYSPARK] Mutable values should not be default argumentsMechCoder2015-08-141-1/+3
| | | | | | Author: MechCoder <manojkumarsivaraj334@gmail.com> Closes #8110 from MechCoder/spark-9828.
* [SPARK-9766] [ML] [PySpark] check and add miss docs for PySpark MLYanbo Liang2015-08-121-1/+2
| | | | | | | | Check and add miss docs for PySpark ML (this issue only check miss docs for o.a.s.ml not o.a.s.mllib). Author: Yanbo Liang <ybliang8@gmail.com> Closes #8059 from yanboliang/SPARK-9766.
* [SPARK-7690] [ML] Multiclass classification EvaluatorRam Sriharsha2015-07-301-0/+66
| | | | | | | | | | | | | | | | | Multiclass Classification Evaluator for ML Pipelines. F1 score, precision, recall, weighted precision and weighted recall are supported as available metrics. Author: Ram Sriharsha <rsriharsha@hw11853.local> Closes #7475 from harsha2010/SPARK-7690 and squashes the following commits: 9bf4ec7 [Ram Sriharsha] fix indentation 3f09a85 [Ram Sriharsha] cleanup doc 16115ae [Ram Sriharsha] code review fixes 032d2a3 [Ram Sriharsha] fix test eec9865 [Ram Sriharsha] Fix Python Indentation 1dbeffd [Ram Sriharsha] Merge branch 'master' into SPARK-7690 68cea85 [Ram Sriharsha] Merge branch 'master' into SPARK-7690 54c03de [Ram Sriharsha] [SPARK-7690][ml][WIP] Multiclass Evaluator for ML Pipeline
* [SPARK-8468] [ML] Take the negative of some metrics in RegressionEvaluator ↵Liang-Chi Hsieh2015-06-201-3/+5
| | | | | | | | | | | | | | | | to get correct cross validation JIRA: https://issues.apache.org/jira/browse/SPARK-8468 Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #6905 from viirya/cv_min and squashes the following commits: 930d3db [Liang-Chi Hsieh] Fix python unit test and add document. d632135 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into cv_min 16e3b2c [Liang-Chi Hsieh] Take the negative instead of reciprocal. c3dd8d9 [Liang-Chi Hsieh] For comments. b5f52c1 [Liang-Chi Hsieh] Add param to CrossValidator for choosing whether to maximize evaulation value.
* [MINOR] fix RegressionEvaluator docXiangrui Meng2015-05-281-1/+1
| | | | | | | | | | | | | | | `make clean html` under `python/doc` returns ~~~ /Users/meng/src/spark/python/pyspark/ml/evaluation.py:docstring of pyspark.ml.evaluation.RegressionEvaluator.setParams:3: WARNING: Definition list ends without a blank line; unexpected unindent. ~~~ harsha2010 Author: Xiangrui Meng <meng@databricks.com> Closes #6469 from mengxr/fix-regression-evaluator-doc and squashes the following commits: 91e2dad [Xiangrui Meng] fix RegressionEvaluator doc
* [SPARK-7833] [ML] Add python wrapper for RegressionEvaluatorRam Sriharsha2015-05-241-2/+66
| | | | | | | | | | Author: Ram Sriharsha <rsriharsha@hw11853.local> Closes #6365 from harsha2010/SPARK-7833 and squashes the following commits: 923f288 [Ram Sriharsha] cleanup 7623b7d [Ram Sriharsha] python style fix 9743f83 [Ram Sriharsha] [SPARK-7833][ml] Add python wrapper for RegressionEvaluator
* [SPARK-7535] [.0] [MLLIB] Audit the pipeline APIs for 1.4Xiangrui Meng2015-05-211-2/+61
| | | | | | | | | | | | | | | | | | | | | | | | Some changes to the pipeilne APIs: 1. Estimator/Transformer/ doesn’t need to extend Params since PipelineStage already does. 1. Move Evaluator to ml.evaluation. 1. Mention larger metric values are better. 1. PipelineModel doc. “compiled” -> “fitted” 1. Hide object PolynomialExpansion. 1. Hide object VectorAssembler. 1. Word2Vec.minCount (and other) -> group param 1. ParamValidators -> DeveloperApi 1. Hide MetadataUtils/SchemaUtils. jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes #6322 from mengxr/SPARK-7535.0 and squashes the following commits: 9e9c7da [Xiangrui Meng] move JavaEvaluator to ml.evaluation as well e179480 [Xiangrui Meng] move Evaluation to ml.evaluation in PySpark 08ef61f [Xiangrui Meng] update pipieline APIs
* [SPARK-7380] [MLLIB] pipeline stages should be copyable in PythonXiangrui Meng2015-05-181-3/+3
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR makes pipeline stages in Python copyable and hence simplifies some implementations. It also includes the following changes: 1. Rename `paramMap` and `defaultParamMap` to `_paramMap` and `_defaultParamMap`, respectively. 2. Accept a list of param maps in `fit`. 3. Use parent uid and name to identify param. jkbradley Author: Xiangrui Meng <meng@databricks.com> Author: Joseph K. Bradley <joseph@databricks.com> Closes #6088 from mengxr/SPARK-7380 and squashes the following commits: 413c463 [Xiangrui Meng] remove unnecessary doc 4159f35 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7380 611c719 [Xiangrui Meng] fix python style 68862b8 [Xiangrui Meng] update _java_obj initialization 927ad19 [Xiangrui Meng] fix ml/tests.py 0138fc3 [Xiangrui Meng] update feature transformers and fix a bug in RegexTokenizer 9ca44fb [Xiangrui Meng] simplify Java wrappers and add tests c7d84ef [Xiangrui Meng] update ml/tests.py to test copy params 7e0d27f [Xiangrui Meng] merge master 46840fb [Xiangrui Meng] update wrappers b6db1ed [Xiangrui Meng] update all self.paramMap to self._paramMap 46cb6ed [Xiangrui Meng] merge master a163413 [Xiangrui Meng] fix style 1042e80 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7380 9630eae [Xiangrui Meng] fix Identifiable._randomUID 13bd70a [Xiangrui Meng] update ml/tests.py 64a536c [Xiangrui Meng] use _fit/_transform/_evaluate to simplify the impl 02abf13 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into copyable-python 66ce18c [Joseph K. Bradley] some cleanups before sending to Xiangrui 7431272 [Joseph K. Bradley] Rebased with master
* [SPARK-7333] [MLLIB] Add BinaryClassificationEvaluator to PySparkXiangrui Meng2015-05-051-0/+107
This PR adds `BinaryClassificationEvaluator` to Python ML Pipelines API, which is a simple wrapper of the Scala implementation. oefirouz Author: Xiangrui Meng <meng@databricks.com> Closes #5885 from mengxr/SPARK-7333 and squashes the following commits: 25d7451 [Xiangrui Meng] fix tests in python 3 babdde7 [Xiangrui Meng] fix doc cb51e6a [Xiangrui Meng] add BinaryClassificationEvaluator in PySpark
generated by cgit v1.2.3 (git 2.39.1) at 2024-09-08 21:10:36 +0000