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

功能介绍

该组件为向量最近邻的训练过程,在计算时与 VectorNearestNeighborPredictBatchOp 配合使用。
支持的距离计算方式包含EUCLIDEAN,COSINE,INNERPRODUCT(内积),CITYBLOCK(曼哈顿距离),JACCARD,PEARSON
默认距离EUCLIDEAN

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 | | —- | —- | —- | —- | —- | —- | —- |

| idCol | id列名 | id列名 | String | ✓ | | |

| selectedCol | 选中的列名 | 计算列对应的列名 | String | ✓ | 所选列类型为 [DENSE_VECTOR, SPARSE_VECTOR, STRING, VECTOR] | |

| metric | 距离度量方式 | 聚类使用的距离类型 | String | | “EUCLIDEAN”, “COSINE”, “INNERPRODUCT”, “CITYBLOCK”, “JACCARD”, “PEARSON” | “EUCLIDEAN” |

代码示例

Python 代码

  1. from pyalink.alink import *
  2. import pandas as pd
  3. useLocalEnv(1)
  4. df = pd.DataFrame([
  5. [0, "0 0 0"],
  6. [1, "1 1 1"],
  7. [2, "2 2 2"]
  8. ])
  9. inOp = BatchOperator.fromDataframe(df, schemaStr='id int, vec string')
  10. train = VectorNearestNeighborTrainBatchOp().setIdCol("id").setSelectedCol("vec").linkFrom(inOp)
  11. predict = VectorNearestNeighborPredictBatchOp().setSelectedCol("vec").setTopN(3).linkFrom(train, inOp)
  12. predict.print()

Java 代码

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

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]”} |