jpmml-sparkml | Java library and command-line application for converting Apache Spark ML pipelines to PMML | Machine Learning library

by jpmml Java Version: 2.4.0 License: AGPL-3.0

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | jpmml-sparkml Summary

jpmml-sparkml is a Java library typically used in Artificial Intelligence, Machine Learning applications. jpmml-sparkml has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub, Maven.

Java library and command-line application for converting Apache Spark ML pipelines to PMML

Support

Quality

Security

License

Reuse

Support

jpmml-sparkml has a low active ecosystem.

It has 265 star(s) with 77 fork(s). There are 27 watchers for this library.

It had no major release in the last 12 months.

There are 17 open issues and 107 have been closed. On average issues are closed in 188 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of jpmml-sparkml is 2.4.0

Quality

jpmml-sparkml has 0 bugs and 0 code smells.

Security

jpmml-sparkml has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

jpmml-sparkml code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

jpmml-sparkml is licensed under the AGPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

jpmml-sparkml releases are available to install and integrate.

Deployable package is available in Maven.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 6048 lines of code, 400 functions and 93 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed jpmml-sparkml and discovered the below as its top functions. This is intended to give you an instant insight into jpmml-sparkml implemented functionality, and help decide if they suit your requirements.

The main entry point
Build PMML model
Load schema
Get the label
Enter a single child node
Checks if is categorical field
Encodes the given schema to a FPGrowthModel
Ensures that the given feature set does not exist
Encodes document features
Checks if a string contains punctuation
Performs the actual encoding on the Indexer model
Enters the tree model
Encode the given schema to the model
Registers features with the encoder
Encodes the model into GeneralRegression model
Encode the features in the PMML format
Encode features in the model
Encodes a feature into a list of features
Returns a list of features that can be used to decode the features of this model
Encodes the features
Registers the outputs for a given label
Encodes the features in the model
Encodes the features in the model
Encodes the given features using the given encoder
Encodes the features
Encodes the maximum absolute features to the model

Get all kandi verified functions for this library.

jpmml-sparkml Key Features

No Key Features are available at this moment for jpmml-sparkml.

jpmml-sparkml Examples and Code Snippets

No Code Snippets are available at this moment for jpmml-sparkml.

Community Discussions

Trending Discussions on jpmml-sparkml

UnmarshalException when running JPMML on Apache Spark

PySpark to PMML - "Field label does not exist" error

JMML Apache Spark org.dmg.pmml.MiningField.setUsageType function not found error

QUESTION

UnmarshalException when running JPMML on Apache Spark

Asked 2018-Oct-11 at 13:07

I am trying to run a code which is using JPPML version 1.4.1 on Apache Spark 2.0.1 . The relevant parts of the pom file are as follows:

...

ANSWER

Answered 2018-Oct-11 at 13:07

Actually, I solved it by deleting pmml-schema-1.2.15.jar and pmml-model-1.2.15.jar in the jars folder in Spark. The reason why it was not working was because I have deleted the files in the Spark folder in the cluster, but not in my local Spark folder (needed to delete both).

Source https://stackoverflow.com/questions/52758358

QUESTION

PySpark to PMML - "Field label does not exist" error

Asked 2017-Jul-01 at 08:52

I am new to PySpark so this might be a basic question. I am trying to export PySpark code to PMML using JPMML-SparkML library. When running an example from JPMML-SparkML website:

...

ANSWER

Answered 2017-Jul-01 at 08:52

You need to provide the column to be predicted as label. Either you can alias the column in dataframe as 'label' and use the Classifier , or can provide the column as labelCol argument in Classifier method.

Source https://stackoverflow.com/questions/44779002

QUESTION

JMML Apache Spark org.dmg.pmml.MiningField.setUsageType function not found error

Asked 2017-Mar-16 at 08:33

I am getting the following error while trying to convert a PipeLine Model in spark to Pmml using JPmml.

java.lang.NoSuchMethodError: org.dmg.pmml.MiningField.setUsageType(Lorg/dmg/pmml/MiningField$UsageType;)Lorg/dmg/pmml/MiningField;

I have added all the dependencies regarding JPmml.

// https://mvnrepository.com/artifact/org.jpmml/jpmml-sparkml libraryDependencies += "org.jpmml" % "jpmml-sparkml" % "1.1.6"

// https://mvnrepository.com/artifact/org.jpmml/pmml-model libraryDependencies += "org.jpmml" % "pmml-model" % "1.3.6"

// https://mvnrepository.com/artifact/org.jpmml/pmml-evaluator libraryDependencies += "org.jpmml" % "pmml-evaluator" % "1.3.5"

...

ANSWER

Answered 2017-Mar-16 at 08:33

I have added all the dependencies regarding JPmml.

You have added all dependencies, but your application can't see them, because in your application classpath, there is an Apache Spark ML provided org.jpmml:pmml-model:1.2.X (has method MiningField#setFieldUsage(MiningField$FieldUsage)), which shadows your org.jpmml:pmml-model:1.3.X (has method MiningField#setUsageType(MiningField$UsageType)): https://issues.apache.org/jira/browse/SPARK-15526

You should stop reinventing the wheel, and use the JPMML-SparkML-Package library. This application classpath/packaging issue is specifically covered in its documentation.

Source https://stackoverflow.com/questions/42827008

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install jpmml-sparkml

You can download it from GitHub, Maven.
You can use jpmml-sparkml like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the jpmml-sparkml component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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