spark PMMLModelExportFactory 源码

2022-10-20
浏览 (217)

spark PMMLModelExportFactory 代码

文件路径：/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/PMMLModelExportFactory.scala

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.spark.mllib.pmml.export

import org.dmg.pmml.regression.RegressionModel

import org.apache.spark.mllib.classification.LogisticRegressionModel
import org.apache.spark.mllib.classification.SVMModel
import org.apache.spark.mllib.clustering.KMeansModel
import org.apache.spark.mllib.regression.LassoModel
import org.apache.spark.mllib.regression.LinearRegressionModel
import org.apache.spark.mllib.regression.RidgeRegressionModel

private[mllib] object PMMLModelExportFactory {

  /**
   * Factory object to help creating the necessary PMMLModelExport implementation
   * taking as input the machine learning model (for example KMeansModel).
   */
  def createPMMLModelExport(model: Any): PMMLModelExport = {
    model match {
      case kmeans: KMeansModel =>
        new KMeansPMMLModelExport(kmeans)
      case linear: LinearRegressionModel =>
        new GeneralizedLinearPMMLModelExport(linear, "linear regression")
      case ridge: RidgeRegressionModel =>
        new GeneralizedLinearPMMLModelExport(ridge, "ridge regression")
      case lasso: LassoModel =>
        new GeneralizedLinearPMMLModelExport(lasso, "lasso regression")
      case svm: SVMModel =>
        new BinaryClassificationPMMLModelExport(
          svm, "linear SVM", RegressionModel.NormalizationMethod.NONE,
          svm.getThreshold.getOrElse(0.0))
      case logistic: LogisticRegressionModel =>
        if (logistic.numClasses == 2) {
          new BinaryClassificationPMMLModelExport(
            logistic, "logistic regression", RegressionModel.NormalizationMethod.LOGIT,
            logistic.getThreshold.getOrElse(0.5))
        } else {
          throw new IllegalArgumentException(
            "PMML Export not supported for Multinomial Logistic Regression")
        }
      case _ =>
        throw new IllegalArgumentException(
          "PMML Export not supported for model: " + model.getClass.getName)
    }
  }

}

相关信息

spark 源码目录

相关文章

spark BinaryClassificationPMMLModelExport 源码

spark GeneralizedLinearPMMLModelExport 源码

spark KMeansPMMLModelExport 源码

spark PMMLModelExport 源码

0 赞

所属分类： 前端技术
本文标签：
版权声明： 原创文章如转载，请注明本文链接: https://www.seaxiang.com/blog/f94f1814af434a23a74fe4c69b9d98fc

热门推荐

1、直接访问google.com
2、 - 优质文章
3、 gate.io
4、 harmony 鸿蒙hdc使用指导
5、 harmony 鸿蒙ArkUI组件（ArkTS）开发常见问题
6、 harmony 鸿蒙初识ArkTS语言
7、 golang
8、 flink kafka connector scan.startup.mode 的几个选项
9、 openharmony
10、 Vue中input框自动聚焦

Loading...