xgboost-predictor | Pure Java implementation of XGBoost predictor | Machine Learning library

 by   h2oai Java Version: 0.3.20 License: Apache-2.0

kandi X-RAY | xgboost-predictor Summary

kandi X-RAY | xgboost-predictor Summary

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

Pure Java implementation of [XGBoost] predictor for online prediction tasks.

            kandi-support Support

              xgboost-predictor has a low active ecosystem.
              It has 32 star(s) with 19 fork(s). There are 94 watchers for this library.
              There were 2 major release(s) in the last 12 months.
              There are 3 open issues and 1 have been closed. On average issues are closed in 405 days. There are 3 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of xgboost-predictor is 0.3.20

            kandi-Quality Quality

              xgboost-predictor has no bugs reported.

            kandi-Security Security

              xgboost-predictor has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              xgboost-predictor is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              xgboost-predictor 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.

            Top functions reviewed by kandi - BETA

            kandi has reviewed xgboost-predictor and discovered the below as its top functions. This is intended to give you an instant insight into xgboost-predictor implemented functionality, and help decide if they suit your requirements.
            • Read the parameter from the model
            • Read UTF - 8 string
            • Read number of bytes
            • Loads the model
            • Fills the internal buffer
            • Read a float array
            • Predict the given feature
            • Returns the predicted value for the specified feature group
            • Returns predictions for the specified feature
            • Return the index of the leaf nodes of the specified feature
            • Initialize the gbm object
            • Compute the weight for a given feature group
            • Read number of bytes from the stream
            • Return the leaf path
            • Use FastMath with FastMath
            • Gets the leaf index
            • Gets the leaf path
            Get all kandi verified functions for this library.

            xgboost-predictor Key Features

            No Key Features are available at this moment for xgboost-predictor.

            xgboost-predictor Examples and Code Snippets

            Getting started,Using Predictor in Java
            Javadot img1Lines of Code : 41dot img1License : Permissive (Apache-2.0)
            copy iconCopy
            package biz.k11i.xgboost.demo;
            import biz.k11i.xgboost.Predictor;
            import biz.k11i.xgboost.util.FVec;
            public class HowToUseXgboostPredictor {
                public static void main(String[] args) throws java.io.IOException {
                    // If you want to use faste  

            Community Discussions

            Trending Discussions on xgboost-predictor


            Is H2O MOJO threadsafe? - xgboost
            Asked 2019-Oct-07 at 18:25

            This is very similar to H2O MOJO thread safe? but for xgboost.

            h2o document Productionizing H2O does not seem to mention anything about it. Is it thread safe to do this in a thread without a lock?



            Answered 2019-Oct-07 at 18:25

            Yes, XGBoost MOJO and XGBoost Java predictor are both thread-safe.

            Source https://stackoverflow.com/questions/58253197

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


            No vulnerabilities reported

            Install xgboost-predictor

            You can download it from GitHub, Maven.
            You can use xgboost-predictor 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 xgboost-predictor 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 .


            Predicts probability or classification.
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          • CLI

            gh repo clone h2oai/xgboost-predictor

          • sshUrl


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