向量最近邻预测 (VectorNearestNeighborPredictBatchOp)

Java 类名:com.alibaba.alink.operator.batch.similarity.VectorNearestNeighborPredictBatchOp

Python 类名:VectorNearestNeighborPredictBatchOp

功能介绍

该组件为向量最近邻预测功能,接收 VectorNearestNeighborTrainBatchOp 训练的模型

该功能由预测时候的topN和radius参数控制, 如果填写了topN,则输出前N个最近邻,如果填写了radius,则输出radius范围内的邻居。如果两个同时设置,则输出radius范围内前N个最近邻。

如果不设置 OutputCol,输出列会替换输入的向量列。

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 所选列类型为 [DENSE_VECTOR, SPARSE_VECTOR, STRING, VECTOR]
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 x >= 1 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

from pyalink.alink import *

import pandas as pd

useLocalEnv(1)

df = pd.DataFrame([
    [0, "0 0 0"],
    [1, "1 1 1"],
    [2, "2 2 2"]
])

inOp = BatchOperator.fromDataframe(df, schemaStr='id int, vec string')
train = VectorNearestNeighborTrainBatchOp().setIdCol("id").setSelectedCol("vec").linkFrom(inOp)
predict = VectorNearestNeighborPredictBatchOp().setSelectedCol("vec").setTopN(3).linkFrom(train, inOp)
predict.print()

Java 代码

import org.apache.flink.types.Row;

import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.similarity.VectorNearestNeighborPredictBatchOp;
import com.alibaba.alink.operator.batch.similarity.VectorNearestNeighborTrainBatchOp;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import org.junit.Test;

import java.util.Arrays;
import java.util.List;

public class VectorNearestNeighborPredictBatchOpTest {
	@Test
	public void testVectorNearestNeighborPredictBatchOp() throws Exception {
		List <Row> df = Arrays.asList(
			Row.of(0, "0 0 0"),
			Row.of(1, "1 1 1"),
			Row.of(2, "2 2 2")
		);
		BatchOperator <?> inOp = new MemSourceBatchOp(df, "id int, vec string");
		BatchOperator <?> train =
			new VectorNearestNeighborTrainBatchOp().setIdCol("id").setSelectedCol("vec").linkFrom(
			inOp);
		BatchOperator <?> predict =
			new VectorNearestNeighborPredictBatchOp().setSelectedCol("vec").setTopN(3).linkFrom(
			train, inOp);
		predict.print();
	}
}

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]”}