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Posted to reviews@spark.apache.org by hhbyyh <gi...@git.apache.org> on 2017/03/13 18:26:56 UTC
[GitHub] spark pull request #17280: [SPARK-19939] [ML] Add support for association ru...
GitHub user hhbyyh opened a pull request:
https://github.com/apache/spark/pull/17280
[SPARK-19939] [ML] Add support for association rules in ML
## What changes were proposed in this pull request?
jira: https://issues.apache.org/jira/browse/SPARK-19939
Adding another essential characteristic for the Association Rule in Spark ml.fpm.
Support is an indication of how frequently the itemset of an association rule appears in the database and suggests if the rules are generally applicable to the dateset. refer to [https://en.wikipedia.org/wiki/Association_rule_learning] for more details.
Before adding support:
rules | confidence
---------|----------------
beer -> soda | 0.5
pecan -> milk | 0.6
After adding support:
rules | confidence | support
-------------------|----------------|-----------
beer -> soda | 0.5 | 0.3
pecan -> milk | 0.6 | 0.01
Thus to allow a better understanding for the generated association rules. This is a new feature and was not included in the original function parity PR.
## How was this patch tested?
existing and new unit test
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/hhbyyh/spark arSupport
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17280.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #17280
----
commit f86c5122eadd9b0a595b776d77d6cdf23ad6731a
Author: Yuhao Yang <yu...@intel.com>
Date: 2017-03-11T01:18:21Z
half
commit bb8ed118619ae93badca06dc346304adce3fa4b7
Author: Yuhao Yang <yu...@intel.com>
Date: 2017-03-11T01:45:33Z
Merge remote-tracking branch 'upstream/master' into arSupport
commit a0ad6628766a5bc556777629fddfc3c61d02d57a
Author: Yuhao Yang <yu...@intel.com>
Date: 2017-03-11T19:01:15Z
Merge remote-tracking branch 'upstream/master' into arSupport
commit 9580aa910523144aba8e4f5a3d9693fe4387f16f
Author: Yuhao Yang <yu...@intel.com>
Date: 2017-03-12T17:50:30Z
add support to association rules
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[GitHub] spark issue #17280: [SPARK-19939] [ML] Add support for association rules in ...
Posted by hhbyyh <gi...@git.apache.org>.
Github user hhbyyh commented on the issue:
https://github.com/apache/spark/pull/17280
I'll first focus on https://github.com/apache/spark/pull/17130 and resolve conflict here.
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Posted by hhbyyh <gi...@git.apache.org>.
Github user hhbyyh commented on the issue:
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Thanks for taking a look @MLnick
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I'll update this after FPGrowth examples and doc merged https://github.com/apache/spark/pull/17130, since there'll be some conflicts.
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[GitHub] spark pull request #17280: [SPARK-19939] [ML] Add support for association ru...
Posted by hhbyyh <gi...@git.apache.org>.
Github user hhbyyh commented on a diff in the pull request:
https://github.com/apache/spark/pull/17280#discussion_r125736603
--- Diff: python/pyspark/ml/fpm.py ---
@@ -186,29 +186,29 @@ class FPGrowth(JavaEstimator, HasItemsCol, HasPredictionCol,
|[z] |
|[x, z, y, r, q, t, p] |
+------------------------+
- >>> fp = FPGrowth(minSupport=0.2, minConfidence=0.7)
+ >>> fp = FPGrowth(minSupport=0.4, minConfidence=0.7)
>>> fpm = fp.fit(data)
>>> fpm.freqItemsets.show(5)
- +---------+----+
- | items|freq|
- +---------+----+
- | [s]| 3|
- | [s, x]| 3|
- |[s, x, z]| 2|
- | [s, z]| 2|
- | [r]| 3|
- +---------+----+
+ +------+----+
+ | items|freq|
+ +------+----+
+ | [s]| 3|
+ |[s, x]| 3|
+ | [r]| 3|
+ | [y]| 3|
+ |[y, x]| 3|
+ +------+----+
--- End diff --
set a higher minSupport to avoid the 0.3333333... in the support column.
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[GitHub] spark pull request #17280: [SPARK-19939] [ML] Add support for association ru...
Posted by MLnick <gi...@git.apache.org>.
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/17280#discussion_r161679593
--- Diff: mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala ---
@@ -319,9 +323,11 @@ object FPGrowthModel extends MLReadable[FPGrowthModel] {
override def load(path: String): FPGrowthModel = {
val metadata = DefaultParamsReader.loadMetadata(path, sc, className)
+ implicit val format = DefaultFormats
+ val numTrainingRecords = (metadata.metadata \ "numTrainingRecords").extract[Long]
--- End diff --
Does this break backward compatibility for loading?
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[GitHub] spark pull request #17280: [SPARK-19939] [ML] Add support for association ru...
Posted by hhbyyh <gi...@git.apache.org>.
Github user hhbyyh commented on a diff in the pull request:
https://github.com/apache/spark/pull/17280#discussion_r161962624
--- Diff: mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala ---
@@ -319,9 +323,11 @@ object FPGrowthModel extends MLReadable[FPGrowthModel] {
override def load(path: String): FPGrowthModel = {
val metadata = DefaultParamsReader.loadMetadata(path, sc, className)
+ implicit val format = DefaultFormats
+ val numTrainingRecords = (metadata.metadata \ "numTrainingRecords").extract[Long]
--- End diff --
Yes it does now. If saving numTrainingRecords to FPGrowthModel looks good, I can update the load logic.
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[GitHub] spark pull request #17280: [SPARK-19939] [ML] Add support for association ru...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17280#discussion_r125154331
--- Diff: python/pyspark/ml/fpm.py ---
@@ -186,29 +186,29 @@ class FPGrowth(JavaEstimator, HasItemsCol, HasPredictionCol,
|[z] |
|[x, z, y, r, q, t, p] |
+------------------------+
- >>> fp = FPGrowth(minSupport=0.2, minConfidence=0.7)
+ >>> fp = FPGrowth(minSupport=0.4, minConfidence=0.7)
>>> fpm = fp.fit(data)
>>> fpm.freqItemsets.show(5)
- +---------+----+
- | items|freq|
- +---------+----+
- | [s]| 3|
- | [s, x]| 3|
- |[s, x, z]| 2|
- | [s, z]| 2|
- | [r]| 3|
- +---------+----+
+ +------+----+
+ | items|freq|
+ +------+----+
+ | [s]| 3|
+ |[s, x]| 3|
+ | [r]| 3|
+ | [y]| 3|
+ |[y, x]| 3|
+ +------+----+
--- End diff --
this seems to change the result quite a bit, is this expected?
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[GitHub] spark issue #17280: [SPARK-19939] [ML] Add support for association rules in ...
Posted by shaneknapp <gi...@git.apache.org>.
Github user shaneknapp commented on the issue:
https://github.com/apache/spark/pull/17280
test this please
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[GitHub] spark issue #17280: [SPARK-19939] [ML] Add support for association rules in ...
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* This patch **fails Scala style tests**.
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[GitHub] spark pull request #17280: [SPARK-19939] [ML] Add support for association ru...
Posted by hhbyyh <gi...@git.apache.org>.
Github user hhbyyh commented on a diff in the pull request:
https://github.com/apache/spark/pull/17280#discussion_r164942458
--- Diff: mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala ---
@@ -319,9 +323,11 @@ object FPGrowthModel extends MLReadable[FPGrowthModel] {
override def load(path: String): FPGrowthModel = {
val metadata = DefaultParamsReader.loadMetadata(path, sc, className)
+ implicit val format = DefaultFormats
+ val numTrainingRecords = (metadata.metadata \ "numTrainingRecords").extract[Long]
--- End diff --
Since we're adding numTrainingRecords to FPGrowthModel and there isn't a proper default number, I suggest we break the backward model loading compatibility. Otherwise we need to fill numTrainingRecords with an incorrect value and will likely create a maintenance trap.
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[GitHub] spark issue #17280: [SPARK-19939] [ML] Add support for association rules in ...
Posted by hhbyyh <gi...@git.apache.org>.
Github user hhbyyh commented on the issue:
https://github.com/apache/spark/pull/17280
Updated to support backward model loading compatibility.
@MLnick @jkbradley
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[GitHub] spark pull request #17280: [SPARK-19939] [ML] Add support for association ru...
Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17280#discussion_r125154338
--- Diff: python/pyspark/ml/fpm.py ---
@@ -186,29 +186,29 @@ class FPGrowth(JavaEstimator, HasItemsCol, HasPredictionCol,
|[z] |
|[x, z, y, r, q, t, p] |
+------------------------+
- >>> fp = FPGrowth(minSupport=0.2, minConfidence=0.7)
+ >>> fp = FPGrowth(minSupport=0.4, minConfidence=0.7)
>>> fpm = fp.fit(data)
>>> fpm.freqItemsets.show(5)
- +---------+----+
- | items|freq|
- +---------+----+
- | [s]| 3|
- | [s, x]| 3|
- |[s, x, z]| 2|
- | [s, z]| 2|
- | [r]| 3|
- +---------+----+
+ +------+----+
+ | items|freq|
+ +------+----+
+ | [s]| 3|
+ |[s, x]| 3|
+ | [r]| 3|
+ | [y]| 3|
+ |[y, x]| 3|
+ +------+----+
--- End diff --
or rather, why is https://github.com/apache/spark/pull/17280/files#diff-b6dbf16870bd2cca9b4140df8aebd681L189 changed?
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[GitHub] spark issue #17280: [SPARK-19939] [ML] Add support for association rules in ...
Posted by hhbyyh <gi...@git.apache.org>.
Github user hhbyyh commented on the issue:
https://github.com/apache/spark/pull/17280
Please advice if this is a good feature to add. If not I'll close it. Thanks.
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