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Posted to reviews@spark.apache.org by zhengruifeng <gi...@git.apache.org> on 2016/05/29 06:09:08 UTC
[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
GitHub user zhengruifeng opened a pull request:
https://github.com/apache/spark/pull/13390
[SPARK-15617][ML][DOC] Clarify that fMeasure in MulticlassMetrics is "micro" f1_score
## What changes were proposed in this pull request?
clarify that fMeasure in MulticlassMetrics is "micro" f1_score.
Because `f1` in `MulticlassClassificationEvaluator` use `mlllib.weightedFMeasure`, so is ignored.
## How was this patch tested?
local build
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/zhengruifeng/spark clarify_f1
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/13390.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 #13390
----
commit 070a85d38cc7a0df3ed9380ff87a46fbbe016323
Author: Zheng RuiFeng <ru...@foxmail.com>
Date: 2016-05-29T05:56:18Z
create pr
commit 11ac84b6578b842b7a67a4ce7181ad5e9dc657cc
Author: Zheng RuiFeng <ru...@foxmail.com>
Date: 2016-05-29T06:05:56Z
create pr 2
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[GitHub] spark issue #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in Multicla...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/13390
That LGTM
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[GitHub] spark issue #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in Multicla...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on the issue:
https://github.com/apache/spark/pull/13390
cc @srowen
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65011674
--- Diff: docs/mllib-evaluation-metrics.md ---
@@ -182,17 +183,22 @@ $$\hat{\delta}(x) = \begin{cases}1 & \text{if $x = 0$}, \\ 0 & \text{otherwise}.
</td>
</tr>
<tr>
- <td>Overall Precision</td>
+ <td>Micro Accuracy</td>
+ <td>$ACC = \frac{TP}{TP + FP} = \frac{1}{N}\sum_{i=0}^{N-1} \hat{\delta}\left(\hat{\mathbf{y}}_i -
+ \mathbf{y}_i\right)$</td>
+ </tr>
+ <tr>
+ <td>Micro Precision</td>
--- End diff --
Hm, on second thought, since we've deprecated precision/recall/F1 for the not-by-label case maybe these should just be removed. Accuracy should stay.
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[GitHub] spark issue #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in Multicla...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/13390
**[Test build #59826 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/59826/consoleFull)** for PR 13390 at commit [`b41226f`](https://github.com/apache/spark/commit/b41226fe88a86035a67669bd3bf9c727621dfd3a).
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[GitHub] spark issue #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in Multicla...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/13390
**[Test build #59831 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/59831/consoleFull)** for PR 13390 at commit [`0427cf8`](https://github.com/apache/spark/commit/0427cf827d5b6c09bb3f7c970880e7d22db9bae7).
* This patch **fails Spark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/13390#issuecomment-222345797
**[Test build #59583 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/59583/consoleFull)** for PR 13390 at commit [`11ac84b`](https://github.com/apache/spark/commit/11ac84b6578b842b7a67a4ce7181ad5e9dc657cc).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65011625
--- Diff: docs/mllib-evaluation-metrics.md ---
@@ -182,17 +183,22 @@ $$\hat{\delta}(x) = \begin{cases}1 & \text{if $x = 0$}, \\ 0 & \text{otherwise}.
</td>
</tr>
<tr>
- <td>Overall Precision</td>
+ <td>Micro Accuracy</td>
+ <td>$ACC = \frac{TP}{TP + FP} = \frac{1}{N}\sum_{i=0}^{N-1} \hat{\delta}\left(\hat{\mathbf{y}}_i -
+ \mathbf{y}_i\right)$</td>
+ </tr>
+ <tr>
+ <td>Micro Precision</td>
--- End diff --
Nit: I might call this "(Micro) Precision" to deemphasize the modifier. I personally had never heard it, and it may be a sklearn-specific description (?) So maybe this makes it more readily understandable as "yes, just the definition you probably expect"
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Posted by AmplabJenkins <gi...@git.apache.org>.
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https://github.com/apache/spark/pull/13390#issuecomment-222364331
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65003197
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/evaluation/MulticlassMetrics.scala ---
@@ -153,7 +153,7 @@ class MulticlassMetrics @Since("1.1.0") (predictionAndLabels: RDD[(Double, Doubl
lazy val recall: Double = accuracy
/**
- * Returns f-measure
+ * Returns micro averaged f1-measure
--- End diff --
There's more to it than just writing the name. It's accurate but not widely known, so this and the docs above should at least include a link and minimal explanation of what it means.
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65030639
--- Diff: docs/mllib-evaluation-metrics.md ---
@@ -182,17 +183,22 @@ $$\hat{\delta}(x) = \begin{cases}1 & \text{if $x = 0$}, \\ 0 & \text{otherwise}.
</td>
</tr>
<tr>
- <td>Overall Precision</td>
+ <td>Micro Accuracy</td>
--- End diff --
Yes, I will drop 'Micro' here
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https://github.com/apache/spark/pull/13390#issuecomment-222364326
**[Test build #59590 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/59590/consoleFull)** for PR 13390 at commit [`cb6735f`](https://github.com/apache/spark/commit/cb6735fa54d567ccdf4c8de91acfe2e76e472deb).
* This patch **fails MiMa tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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**[Test build #59836 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/59836/consoleFull)** for PR 13390 at commit [`b4d5811`](https://github.com/apache/spark/commit/b4d5811d2889c4238c29df59c9cbce256d325367).
* This patch passes all tests.
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65011630
--- Diff: mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala ---
@@ -41,6 +41,10 @@ class MulticlassClassificationEvaluator @Since("1.5.0") (@Since("1.5.0") overrid
/**
* param for metric name in evaluation (supports `"f1"` (default), `"precision"`, `"recall"`,
* `"weightedPrecision"`, `"weightedRecall"`, `"accuracy"`)
+ * Note: `"f1"` here means weighted averaged f1-measure, while the `fMeasure` in
--- End diff --
This applies to f1, precision and recall equally
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[GitHub] spark pull request #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in M...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65692163
--- Diff: mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala ---
@@ -39,16 +39,16 @@ class MulticlassClassificationEvaluator @Since("1.5.0") (@Since("1.5.0") overrid
def this() = this(Identifiable.randomUID("mcEval"))
/**
- * param for metric name in evaluation (supports `"f1"` (default), `"precision"`, `"recall"`,
- * `"weightedPrecision"`, `"weightedRecall"`, `"accuracy"`)
+ * param for metric name in evaluation (supports `"f1"` (default), `"weightedPrecision"`,
--- End diff --
OK, I will rename `f1` to `weightedF1Measure`
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https://github.com/apache/spark/pull/13390#issuecomment-222366276
**[Test build #59591 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/59591/consoleFull)** for PR 13390 at commit [`cb6735f`](https://github.com/apache/spark/commit/cb6735fa54d567ccdf4c8de91acfe2e76e472deb).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on the pull request:
https://github.com/apache/spark/pull/13390#issuecomment-222364467
test this please
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65011611
--- Diff: docs/mllib-evaluation-metrics.md ---
@@ -182,17 +183,22 @@ $$\hat{\delta}(x) = \begin{cases}1 & \text{if $x = 0$}, \\ 0 & \text{otherwise}.
</td>
</tr>
<tr>
- <td>Overall Precision</td>
+ <td>Micro Accuracy</td>
--- End diff --
"Micro" doesn't apply to accuracy, as I understand the definition.
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65011652
--- Diff: docs/mllib-evaluation-metrics.md ---
@@ -136,6 +136,7 @@ for all other classes. So, a true positive occurs whenever the prediction and th
occurs when neither the prediction nor the label take on the value of a given class. By this convention, there can be
multiple true negatives for a given data sample. The extension of false negatives and false positives from the former
definitions of positive and negative labels is straightforward.
+Note that the [micro averaged](http://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html) accuracy, precision, recall, and F1-measure are the same.
--- End diff --
I think I might leave this out. Actually, overall precision/recall/F1 for multiclass are deprecated anyway.
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65011713
--- Diff: mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala ---
@@ -41,6 +41,10 @@ class MulticlassClassificationEvaluator @Since("1.5.0") (@Since("1.5.0") overrid
/**
* param for metric name in evaluation (supports `"f1"` (default), `"precision"`, `"recall"`,
* `"weightedPrecision"`, `"weightedRecall"`, `"accuracy"`)
+ * Note: `"f1"` here means weighted averaged f1-measure, while the `fMeasure` in
--- End diff --
Also, fMeasure isn't a supported value here? or do I miss it? f1 is a measure. Here again I wonder if it's worth documenting it, since f1 / precision / recall are deprecated.
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[GitHub] spark issue #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in Multicla...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/13390
**[Test build #59832 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/59832/consoleFull)** for PR 13390 at commit [`42ed0b9`](https://github.com/apache/spark/commit/42ed0b97690545279b2faa99166007b56ef29a3b).
* This patch **fails Spark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/13390#issuecomment-222366304
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65005147
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/evaluation/MulticlassMetrics.scala ---
@@ -153,7 +153,7 @@ class MulticlassMetrics @Since("1.1.0") (predictionAndLabels: RDD[(Double, Doubl
lazy val recall: Double = accuracy
/**
- * Returns f-measure
+ * Returns micro averaged f1-measure
--- End diff --
Thanks, I will detail it
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[GitHub] spark pull request #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in M...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/13390
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[GitHub] spark issue #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in Multicla...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/13390
**[Test build #59826 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/59826/consoleFull)** for PR 13390 at commit [`b41226f`](https://github.com/apache/spark/commit/b41226fe88a86035a67669bd3bf9c727621dfd3a).
* This patch **fails PySpark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in M...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65570795
--- Diff: mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala ---
@@ -39,16 +39,16 @@ class MulticlassClassificationEvaluator @Since("1.5.0") (@Since("1.5.0") overrid
def this() = this(Identifiable.randomUID("mcEval"))
/**
- * param for metric name in evaluation (supports `"f1"` (default), `"precision"`, `"recall"`,
- * `"weightedPrecision"`, `"weightedRecall"`, `"accuracy"`)
+ * param for metric name in evaluation (supports `"f1"` (default), `"weightedPrecision"`,
--- End diff --
ah, so f1 = weightedF1Measure? OK
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[GitHub] spark issue #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in Multicla...
Posted by SparkQA <gi...@git.apache.org>.
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https://github.com/apache/spark/pull/13390
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[GitHub] spark issue #13390: [SPARK-15617][ML][DOC] Clarify that fMeasure in Multicla...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on the issue:
https://github.com/apache/spark/pull/13390
Merged to master/2.0
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[GitHub] spark pull request: [SPARK-15617][ML][DOC] Clarify that fMeasure i...
Posted by zhengruifeng <gi...@git.apache.org>.
Github user zhengruifeng commented on a diff in the pull request:
https://github.com/apache/spark/pull/13390#discussion_r65027076
--- Diff: docs/mllib-evaluation-metrics.md ---
@@ -182,17 +183,22 @@ $$\hat{\delta}(x) = \begin{cases}1 & \text{if $x = 0$}, \\ 0 & \text{otherwise}.
</td>
</tr>
<tr>
- <td>Overall Precision</td>
+ <td>Micro Accuracy</td>
+ <td>$ACC = \frac{TP}{TP + FP} = \frac{1}{N}\sum_{i=0}^{N-1} \hat{\delta}\left(\hat{\mathbf{y}}_i -
+ \mathbf{y}_i\right)$</td>
+ </tr>
+ <tr>
+ <td>Micro Precision</td>
--- End diff --
The term `Micro Precision` is already used in the part of Multilabel classification, so I rename it here.
I agreed that we remove `precision/recall/F1` here.
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