[jira] [Updated] (SPARK-38243) Unintended exception thrown in pyspark.ml.LogisticRegression.getThreshold
[
https://issues.apache.org/jira/browse/SPARK-38243?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean R. Owen updated SPARK-38243:
-
Priority: Trivial (was: Minor)
> Unintended exception thrown in pyspark.ml.LogisticRegression.getThreshold
> -
>
> Key: SPARK-38243
> URL: https://issues.apache.org/jira/browse/SPARK-38243
> Project: Spark
> Issue Type: Bug
> Components: ML, PySpark
>Affects Versions: 2.4.0, 3.1.0, 3.2.0, 3.3.0
>Reporter: Maciej Szymkiewicz
>Assignee: Maciej Szymkiewicz
>Priority: Trivial
> Fix For: 3.3.0
>
>
> If {{LogisticRegression.getThreshold}} is called with model having multiple
> thresholds we suppose to raise an exception,
> {code:python}
> ValueError: Logistic Regression getThreshold only applies to binary
> classification ...
> {code}
> However, {{thresholds}} ({{{}List[float]{}}}) are incorrectly passed to
> {{{}str.join{}}}, resulting in unintended {{TypeError}}
> {code:python}
> >>> from pyspark.ml.classification import LogisticRegression
> ...
> ... model = LogisticRegression(thresholds=[1.0, 2.0, 3.0])
> >>> model.getThreshold()
> Traceback (most recent call last):
> Input In [7] in
> model.getThreshold()
> File /path/to/spark/python/pyspark/ml/classification.py:1003 in getThreshold
> + ",".join(ts)
> Type Error: sequence item 0: expected str instance, float found
> {code}
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[jira] [Updated] (SPARK-38243) Unintended exception thrown in pyspark.ml.LogisticRegression.getThreshold
[
https://issues.apache.org/jira/browse/SPARK-38243?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Maciej Szymkiewicz updated SPARK-38243:
---
Description:
If {{LogisticRegression.getThreshold}} is called with model having multiple
thresholds we suppose to raise an exception,
{code:python}
ValueError: Logistic Regression getThreshold only applies to binary
classification ...
{code}
However, {{thresholds}} ({{{}List[float]{}}}) are incorrectly passed to
{{{}str.join{}}}, resulting in unintended {{TypeError}}
{code:python}
>>> from pyspark.ml.classification import LogisticRegression
...
... model = LogisticRegression(thresholds=[1.0, 2.0, 3.0])
>>> model.getThreshold()
Traceback (most recent call last):
Input In [7] in
model.getThreshold()
File /path/to/spark/python/pyspark/ml/classification.py:1003 in getThreshold
+ ",".join(ts)
Type Error: sequence item 0: expected str instance, float found
{code}
was:
If {{LogisticRegression.getThreshold}} is called with model having multiple
thresholds we suppose to raise an exception,
{code:python}
ValueError: Logistic Regression getThreshold only applies to binary
classification ...
{code}
However, {{thresholds}} ({{{}List[float]{}}}) are incorrectly passed to
{{{}str.join{}}}, resulting in unintended {{TypeError}}
{code:python}
>>> from pyspark.ml.classification import LogisticRegression
...
... model = LogisticRegression(thresholds=[1.0, 2.0, 3.0])
>>> model.getThreshold()
Traceback (most recent call last):
Input In [7] in
model.getThreshold()
File ~/Workspace/spark/python/pyspark/ml/classification.py:1003 in
getThreshold
+ ",".join(ts)
Type Error: sequence item 0: expected str instance, float found
{code}
> Unintended exception thrown in pyspark.ml.LogisticRegression.getThreshold
> -
>
> Key: SPARK-38243
> URL: https://issues.apache.org/jira/browse/SPARK-38243
> Project: Spark
> Issue Type: Bug
> Components: ML, PySpark
>Affects Versions: 2.4.0, 3.1.0, 3.2.0, 3.3.0
>Reporter: Maciej Szymkiewicz
>Priority: Minor
>
> If {{LogisticRegression.getThreshold}} is called with model having multiple
> thresholds we suppose to raise an exception,
> {code:python}
> ValueError: Logistic Regression getThreshold only applies to binary
> classification ...
> {code}
> However, {{thresholds}} ({{{}List[float]{}}}) are incorrectly passed to
> {{{}str.join{}}}, resulting in unintended {{TypeError}}
> {code:python}
> >>> from pyspark.ml.classification import LogisticRegression
> ...
> ... model = LogisticRegression(thresholds=[1.0, 2.0, 3.0])
> >>> model.getThreshold()
> Traceback (most recent call last):
> Input In [7] in
> model.getThreshold()
> File /path/to/spark/python/pyspark/ml/classification.py:1003 in getThreshold
> + ",".join(ts)
> Type Error: sequence item 0: expected str instance, float found
> {code}
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[jira] [Updated] (SPARK-38243) Unintended exception thrown in pyspark.ml.LogisticRegression.getThreshold
[
https://issues.apache.org/jira/browse/SPARK-38243?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Maciej Szymkiewicz updated SPARK-38243:
---
Description:
If {{LogisticRegression.getThreshold}} is called with model having multiple
thresholds we suppose to raise an exception,
{code:python}
ValueError: Logistic Regression getThreshold only applies to binary
classification ...
{code}
However, {{thresholds}} ({{{}List[float]{}}}) are incorrectly passed to
{{{}str.join{}}}, resulting in unintended {{TypeError}}
{code:python}
>>> from pyspark.ml.classification import LogisticRegression
...
... model = LogisticRegression(thresholds=[1.0, 2.0, 3.0])
>>> model.getThreshold()
Traceback (most recent call last):
Input In [7] in
model.getThreshold()
File ~/Workspace/spark/python/pyspark/ml/classification.py:1003 in
getThreshold
+ ",".join(ts)
Type Error: sequence item 0: expected str instance, float found
{code}
was:
If {{LogisticRegression.getThreshold}} is called with model having multiple
thresholds we suppose to raise an exception,
{code:python}
ValueError: Logistic Regression getThreshold only applies to binary
classification ...
{code}
However, {{thresholds}} ({{{}List[float]{}}}) are incorrectly passed to
{{{}str.format{}}}, resulting in unintended {{TypeError}}
{code:python}
>>> from pyspark.ml.classification import LogisticRegression
...
... model = LogisticRegression(thresholds=[1.0, 2.0, 3.0])
>>> model.getThreshold()
Traceback (most recent call last):
Input In [7] in
model.getThreshold()
File ~/Workspace/spark/python/pyspark/ml/classification.py:1003 in
getThreshold
+ ",".join(ts)
Type Error: sequence item 0: expected str instance, float found
{code}
> Unintended exception thrown in pyspark.ml.LogisticRegression.getThreshold
> -
>
> Key: SPARK-38243
> URL: https://issues.apache.org/jira/browse/SPARK-38243
> Project: Spark
> Issue Type: Bug
> Components: ML, PySpark
>Affects Versions: 2.4.0, 3.1.0, 3.2.0, 3.3.0
>Reporter: Maciej Szymkiewicz
>Priority: Minor
>
> If {{LogisticRegression.getThreshold}} is called with model having multiple
> thresholds we suppose to raise an exception,
> {code:python}
> ValueError: Logistic Regression getThreshold only applies to binary
> classification ...
> {code}
> However, {{thresholds}} ({{{}List[float]{}}}) are incorrectly passed to
> {{{}str.join{}}}, resulting in unintended {{TypeError}}
> {code:python}
> >>> from pyspark.ml.classification import LogisticRegression
> ...
> ... model = LogisticRegression(thresholds=[1.0, 2.0, 3.0])
> >>> model.getThreshold()
> Traceback (most recent call last):
> Input In [7] in
> model.getThreshold()
> File ~/Workspace/spark/python/pyspark/ml/classification.py:1003 in
> getThreshold
> + ",".join(ts)
> Type Error: sequence item 0: expected str instance, float found
> {code}
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