Java 类名：com.alibaba.alink.operator.batch.similarity.VectorApproxNearestNeighborPredictBatchOp
Python 类名：VectorApproxNearestNeighborPredictBatchOp

功能介绍

该功能由训练和预测组成，该组件为预测功能
该功能由预测时候的topN和radius参数控制, 如果填写了topN，则输出最近邻，如果填写了radius，则输出radius范围内的邻居。

参数说明

| 名称 | 中文名称 | 描述 | 类型 | 是否必须？ | 取值范围 | 默认值 | | —- | —- | —- | —- | —- | —- | —- |

| selectedCol | 选中的列名 | 计算列对应的列名 | String | ✓ | | |

| modelFilePath | 模型的文件路径 | 模型的文件路径 | String | | | null |

| outputCol | 输出结果列 | 输出结果列列名，可选，默认null | String | | | null |

| radius | radius值 | radius值 | Double | | | null |

| reservedCols | 算法保留列名 | 算法保留列 | String[] | | | null |

| topN | TopN的值 | TopN的值 | Integer | | [1, +inf) | null |

| numThreads | 组件多线程线程个数 | 组件多线程线程个数 | Integer | | | 1 |

代码示例

Python 代码

  1. from pyalink.alink import *
  3. import pandas as pd
  5. useLocalEnv(1)
  7. df = pd.DataFrame([
  8.     [0, "0 0 0"],
  9.     [1, "1 1 1"],
  10.     [2, "2 2 2"]
  11. ])
  13. inOp = BatchOperator.fromDataframe(df, schemaStr='id int, vec string')
  14. train = VectorApproxNearestNeighborTrainBatchOp().setIdCol("id").setSelectedCol("vec").linkFrom(inOp)
  15. predict = VectorApproxNearestNeighborPredictBatchOp().setSelectedCol("vec").setTopN(3).linkFrom(train, inOp)
  16. predict.print()

Java 代码

  1. import org.apache.flink.types.Row;
  3. import com.alibaba.alink.operator.batch.BatchOperator;
  4. import com.alibaba.alink.operator.batch.similarity.VectorApproxNearestNeighborPredictBatchOp;
  5. import com.alibaba.alink.operator.batch.similarity.VectorApproxNearestNeighborTrainBatchOp;
  6. import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
  7. import org.junit.Test;
  9. import java.util.Arrays;
  10. import java.util.List;
  12. public class VectorApproxNearestNeighborPredictBatchOpTest {
  13.     @Test
  14.     public void testVectorApproxNearestNeighborPredictBatchOp() throws Exception {
  15.         List <Row> df = Arrays.asList(
  16.             Row.of(0, "0 0 0"),
  17.             Row.of(1, "1 1 1"),
  18.             Row.of(2, "2 2 2")
  19.         );
  20.         BatchOperator <?> inOp = new MemSourceBatchOp(df, "id int, vec string");
  21.         BatchOperator <?> train = new VectorApproxNearestNeighborTrainBatchOp().setIdCol("id").setSelectedCol("vec")
  22.             .linkFrom(inOp);
  23.         BatchOperator <?> predict = new VectorApproxNearestNeighborPredictBatchOp().setSelectedCol("vec").setTopN(3)
  24.             .linkFrom(train, inOp);
  25.         predict.print();
  26.     }
  27. }

运行结果

| id | vec | | —- | —- |

| 0 | {“ID”:”[0,1,2]”,”METRIC”:”[0.0,1.7320508075688772,3.4641016151377544]”} |

| 1 | {“ID”:”[1,2,0]”,”METRIC”:”[0.0,1.7320508075688772,1.7320508075688772]”} |

| 2 | {“ID”:”[2,1,0]”,”METRIC”:”[0.0,1.7320508075688772,3.4641016151377544]”} |