jpmml-lightgbm:Java库和命令行应用程序,用于将LightGBM模型转换为PMML

上传者: 42109639 | 上传时间: 2022-05-15 16:49:04 | 文件大小: 1.16MB | 文件类型: ZIP
JPMML-LightGBM Java库和命令行应用程序,用于将模型转换为PMML。 先决条件 LightGBM 2.0.0或更高版本。 Java 1.8或更高版本。 安装 输入项目根目录并使用构建: mvn clean install 构建生成可执行的uber-JAR文件target/jpmml-lightgbm-executable-1.3-SNAPSHOT.jar 。 用法 典型的工作流程可以总结如下: 使用LightGBM训练模型。 将模型保存到本地文件系统中的文本文件中。 使用JPMML-LightGBM命令行转换器应用程序将此文本文件转换为PMML文件。 LightGBM操作方面 使用软件包为示例波士顿住房数据集训练回归模型: from sklearn . datasets import load_boston boston = load_boston () fr

文件下载

资源详情

[{"title":"( 92 个子文件 1.16MB ) jpmml-lightgbm:Java库和命令行应用程序,用于将LightGBM模型转换为PMML","children":[{"title":"jpmml-lightgbm-master","children":[{"title":"pom.xml <span style='color:#111;'> 5.94KB </span>","children":null,"spread":false},{"title":"NOTICE.txt <span style='color:#111;'> 11.28KB </span>","children":null,"spread":false},{"title":".github","children":[{"title":"workflows","children":[{"title":"maven.yml <span style='color:#111;'> 485B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"src","children":[{"title":"test","children":[{"title":"resources","children":[{"title":"main.py <span style='color:#111;'> 8.45KB </span>","children":null,"spread":false},{"title":"csv","children":[{"title":"ClassificationVersicolor.csv <span style='color:#111;'> 6.01KB </span>","children":null,"spread":false},{"title":"RegressionAutoNA@17.csv <span style='color:#111;'> 7.24KB </span>","children":null,"spread":false},{"title":"VisitNA.csv <span style='color:#111;'> 94.95KB </span>","children":null,"spread":false},{"title":"RegressionHousing@31.csv <span style='color:#111;'> 9.19KB </span>","children":null,"spread":false},{"title":"Iris.csv <span style='color:#111;'> 3.63KB </span>","children":null,"spread":false},{"title":"RegressionHousingNA.csv <span style='color:#111;'> 9.15KB </span>","children":null,"spread":false},{"title":"RFClassificationIris.csv <span style='color:#111;'> 8.97KB </span>","children":null,"spread":false},{"title":"ClassificationAudit.csv <span style='color:#111;'> 75.83KB </span>","children":null,"spread":false},{"title":"ClassificationAuditInvalid.csv <span style='color:#111;'> 75.99KB </span>","children":null,"spread":false},{"title":"ClassificationAudit@17.csv <span style='color:#111;'> 75.23KB </span>","children":null,"spread":false},{"title":"RegressionHousing.csv <span style='color:#111;'> 9.16KB </span>","children":null,"spread":false},{"title":"Visit.csv <span style='color:#111;'> 93.17KB </span>","children":null,"spread":false},{"title":"ClassificationAuditBinNA.csv <span style='color:#111;'> 75.64KB </span>","children":null,"spread":false},{"title":"RFClassificationAudit.csv <span style='color:#111;'> 75.40KB </span>","children":null,"spread":false},{"title":"ClassificationIris.csv <span style='color:#111;'> 9.65KB </span>","children":null,"spread":false},{"title":"RegressionAuto.csv <span style='color:#111;'> 7.24KB </span>","children":null,"spread":false},{"title":"AutoNA.csv <span style='color:#111;'> 10.89KB </span>","children":null,"spread":false},{"title":"RegressionAutoDirectNA.csv <span style='color:#111;'> 7.22KB </span>","children":null,"spread":false},{"title":"ClassificationAuditNA@17.csv <span style='color:#111;'> 75.20KB </span>","children":null,"spread":false},{"title":"HousingNA.csv <span style='color:#111;'> 32.74KB </span>","children":null,"spread":false},{"title":"ClassificationIrisNA@7.csv <span style='color:#111;'> 8.90KB </span>","children":null,"spread":false},{"title":"Housing.csv <span style='color:#111;'> 40.39KB </span>","children":null,"spread":false},{"title":"RegressionAuto@17.csv <span style='color:#111;'> 7.23KB </span>","children":null,"spread":false},{"title":"Audit.csv <span style='color:#111;'> 114.80KB </span>","children":null,"spread":false},{"title":"ClassificationVersicolor@9.csv <span style='color:#111;'> 5.98KB </span>","children":null,"spread":false},{"title":"RegressionVisit.csv <span style='color:#111;'> 40.11KB </span>","children":null,"spread":false},{"title":"ClassificationIrisNA.csv <span style='color:#111;'> 8.89KB </span>","children":null,"spread":false},{"title":"AuditInvalid.csv <span style='color:#111;'> 112.24KB </span>","children":null,"spread":false},{"title":"RegressionAutoDirect.csv <span style='color:#111;'> 7.24KB </span>","children":null,"spread":false},{"title":"IrisNA.csv <span style='color:#111;'> 3.65KB </span>","children":null,"spread":false},{"title":"Versicolor.csv <span style='color:#111;'> 3.15KB </span>","children":null,"spread":false},{"title":"ClassificationAuditBin.csv <span style='color:#111;'> 75.75KB </span>","children":null,"spread":false},{"title":"Auto.csv <span style='color:#111;'> 10.67KB </span>","children":null,"spread":false},{"title":"RegressionHousingNA@31.csv <span style='color:#111;'> 9.18KB </span>","children":null,"spread":false},{"title":"ClassificationIris@7.csv <span style='color:#111;'> 8.87KB </span>","children":null,"spread":false},{"title":"AuditNA.csv <span style='color:#111;'> 105.96KB </span>","children":null,"spread":false},{"title":"RegressionVisitNA@31.csv <span style='color:#111;'> 40.21KB </span>","children":null,"spread":false},{"title":"RegressionVisit@31.csv <span style='color:#111;'> 39.92KB </span>","children":null,"spread":false},{"title":"RFRegressionAuto.csv <span style='color:#111;'> 7.24KB </span>","children":null,"spread":false},{"title":"RegressionVisitNA.csv <span style='color:#111;'> 40.30KB </span>","children":null,"spread":false},{"title":"ClassificationAuditNA.csv <span style='color:#111;'> 75.68KB </span>","children":null,"spread":false},{"title":"RegressionAutoNA.csv <span style='color:#111;'> 7.22KB </span>","children":null,"spread":false}],"spread":false},{"title":"data.R <span style='color:#111;'> 1.21KB </span>","children":null,"spread":false},{"title":"lgbm","children":[{"title":"ClassificationIris.txt <span style='color:#111;'> 435.73KB </span>","children":null,"spread":false},{"title":"RegressionAuto.txt <span style='color:#111;'> 45.08KB </span>","children":null,"spread":false},{"title":"ClassificationIrisNA.txt <span style='color:#111;'> 25.83KB </span>","children":null,"spread":false},{"title":"RegressionHousingNA.txt <span style='color:#111;'> 60.90KB </span>","children":null,"spread":false},{"title":"RFClassificationIris.txt <span style='color:#111;'> 278.60KB </span>","children":null,"spread":false},{"title":"RegressionAutoDirectNA.txt <span style='color:#111;'> 45.49KB </span>","children":null,"spread":false},{"title":"ClassificationVersicolor.txt <span style='color:#111;'> 10.61KB </span>","children":null,"spread":false},{"title":"ClassificationAuditBinNA.txt <span style='color:#111;'> 102.49KB </span>","children":null,"spread":false},{"title":"ClassificationAuditNA.txt <span style='color:#111;'> 103.44KB </span>","children":null,"spread":false},{"title":"ClassificationAuditBin.txt <span style='color:#111;'> 102.00KB </span>","children":null,"spread":false},{"title":"RFRegressionAuto.txt <span style='color:#111;'> 33.90KB </span>","children":null,"spread":false},{"title":"RegressionHousing.txt <span style='color:#111;'> 90.30KB </span>","children":null,"spread":false},{"title":"RegressionAutoDirect.txt <span style='color:#111;'> 45.21KB </span>","children":null,"spread":false},{"title":"RFClassificationAudit.txt <span style='color:#111;'> 101.42KB </span>","children":null,"spread":false},{"title":"RegressionAutoNA.txt <span style='color:#111;'> 45.43KB </span>","children":null,"spread":false},{"title":"ClassificationAudit.txt <span style='color:#111;'> 103.31KB </span>","children":null,"spread":false},{"title":"RegressionVisit.txt <span style='color:#111;'> 233.88KB </span>","children":null,"spread":false},{"title":"RegressionVisitNA.txt <span style='color:#111;'> 232.45KB </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"java","children":[{"title":"org","children":[{"title":"jpmml","children":[{"title":"lightgbm","children":[{"title":"ClassificationTest.java <span style='color:#111;'> 3.58KB </span>","children":null,"spread":false},{"title":"PandasDummiesTest.java <span style='color:#111;'> 4.32KB </span>","children":null,"spread":false},{"title":"LightGBMTest.java <span style='color:#111;'> 1.51KB </span>","children":null,"spread":false},{"title":"RegressionTest.java <span style='color:#111;'> 3.73KB </span>","children":null,"spread":false},{"title":"PandasCategoricalParserTest.java <span style='color:#111;'> 1.70KB </span>","children":null,"spread":false},{"title":"LightGBMTestBatch.java <span style='color:#111;'> 3.00KB </span>","children":null,"spread":false},{"title":"LightGBMUtilTest.java <span style='color:#111;'> 1.03KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}],"spread":true}],"spread":true},{"title":"main","children":[{"title":"javacc","children":[{"title":"pandas_categorical.jj <span style='color:#111;'> 2.53KB </span>","children":null,"spread":false}],"spread":true},{"title":"java","children":[{"title":"org","children":[{"title":"jpmml","children":[{"title":"lightgbm","children":[{"title":"BinaryCategoricalFeature.java <span style='color:#111;'> 1.16KB </span>","children":null,"spread":false},{"title":"LightGBMUtil.java <span style='color:#111;'> 6.05KB </span>","children":null,"spread":false},{"title":"HasLightGBMOptions.java <span style='color:#111;'> 1.33KB </span>","children":null,"spread":false},{"title":"Section.java <span style='color:#111;'> 3.24KB </span>","children":null,"spread":false},{"title":"LightGBMEncoder.java <span style='color:#111;'> 886B </span>","children":null,"spread":false},{"title":"Tree.java <span style='color:#111;'> 12.30KB </span>","children":null,"spread":false},{"title":"DirectCategoricalFeature.java <span style='color:#111;'> 1.06KB </span>","children":null,"spread":false},{"title":"PoissonRegression.java <span style='color:#111;'> 1.68KB </span>","children":null,"spread":false},{"title":"Lambdarank.java <span style='color:#111;'> 910B </span>","children":null,"spread":false},{"title":"ObjectiveFunction.java <span style='color:#111;'> 2.74KB </span>","children":null,"spread":false},{"title":"BinomialLogisticRegression.java <span style='color:#111;'> 1.86KB </span>","children":null,"spread":false},{"title":"visitors","children":[{"title":"TreeModelCompactor.java <span style='color:#111;'> 3.35KB </span>","children":null,"spread":false}],"spread":false},{"title":"Classification.java <span style='color:#111;'> 2.04KB </span>","children":null,"spread":false},{"title":"Regression.java <span style='color:#111;'> 1.83KB </span>","children":null,"spread":false},{"title":"Main.java <span style='color:#111;'> 4.79KB </span>","children":null,"spread":false},{"title":"MultinomialLogisticRegression.java <span style='color:#111;'> 2.37KB </span>","children":null,"spread":false},{"title":"GBDT.java <span style='color:#111;'> 15.27KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}],"spread":true}],"spread":true}],"spread":true}],"spread":true},{"title":"README.md <span style='color:#111;'> 2.95KB </span>","children":null,"spread":false},{"title":"LICENSE.txt <span style='color:#111;'> 33.71KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明