jpmml-sklearn | Java library and command-line application | Machine Learning library

by jpmml Java Version: 1.7.53 License: AGPL-3.0

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | jpmml-sklearn Summary

jpmml-sklearn is a Java library typically used in Artificial Intelligence, Machine Learning applications. jpmml-sklearn 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 Scikit-Learn pipelines to PMML

Support

Quality

Security

License

Reuse

Support

jpmml-sklearn has a low active ecosystem.

It has 507 star(s) with 116 fork(s). There are 24 watchers for this library.

It had no major release in the last 12 months.

There are 14 open issues and 155 have been closed. On average issues are closed in 357 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of jpmml-sklearn is 1.7.53

Quality

jpmml-sklearn has 0 bugs and 0 code smells.

Security

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

jpmml-sklearn code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

jpmml-sklearn 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-sklearn 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.

jpmml-sklearn saves you 6531 person hours of effort in developing the same functionality from scratch.

It has 17052 lines of code, 1556 functions and 304 files.

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

Top functions reviewed by kandi - BETA

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

Encodes the given Schema into a StreamModel
Compare two version strings
Correct average path length
Parses a version number from a string
Encodes the features
Helper to convert values into a map
Transforms a map into a transformed map
Encodes the given set of features
Encodes the features provided by the sklearned feature
Encode a set of features
Encodes a list of features to features
Encode a set of features
Encode a set of feature features
Returns the distribution model for the given schema
Returns the categorical categories
Encodes this model into a training model
Performs the actual encoding of the feature
Encodes a set of features
Encodes a list of features using the sklearner algorithm
Converts a set of features to features
Encode a MiningModel into a StreamModel
Encodes the features
Encodes a set of features
Creates a mean series from a data frame
Encodes the model into model
Encodes the features to features

Get all kandi verified functions for this library.

jpmml-sklearn Key Features

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

jpmml-sklearn Examples and Code Snippets

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

Community Discussions

Trending Discussions on jpmml-sklearn

Parse xml file in pandas

How to make predictions with Syncfusion PMML from a Neural Network trained with sklearn MLPClassifier?

QUESTION

Parse xml file in pandas

Asked 2022-Feb-15 at 14:22

I have this xml file (it's called "LogReg.xml" and it contains some information about a logistic regression (I am interested in the name of the features and their coefficient - I'll explain in more detail below):

...

ANSWER

Answered 2022-Feb-15 at 14:22

I'm not sure you need pandas for this, but you do need to handle the namespaces in your xml.

Try something along these lines:

Source https://stackoverflow.com/questions/71127261

QUESTION

How to make predictions with Syncfusion PMML from a Neural Network trained with sklearn MLPClassifier?

Asked 2020-Jan-24 at 04:19

I trained a model in Python using sklearn.neural_network.MLPClassifier (0.20.3) and saved it in PMML format using sklearn2pmml (0.48.0). The saved PMML model works as expected when loaded in Java using org.jpmml:pmml-evaluator:1.4.14.

I now want to load the PMML model and make predictions in C# using the Syncfusion package:

...

ANSWER

Answered 2020-Jan-23 at 11:49

We have checked sample PMML file using NeuralNetworkModelEvaluator and we couldn’t reproduce the issue. Can you share your PMML file to check our side and provide you the solution sooner.

Also, we would suggest you to try the below code,

Source https://stackoverflow.com/questions/59853972

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

Vulnerabilities

No vulnerabilities reported

Install jpmml-sklearn

You can download it from GitHub, Maven.
You can use jpmml-sklearn 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-sklearn 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 .

Find more information at: