向量缺失值填充预测 (VectorImputerPredictBatchOp)

Java 类名：com.alibaba.alink.operator.batch.dataproc.vector.VectorImputerPredictBatchOp
Python 类名：VectorImputerPredictBatchOp

功能介绍

使用 Vector 缺失值填充模型对Vector数据进行数据填充。
输入数据包含 VectorImputerTrainBatchOp 输出的模型和要处理的数据。

参数说明

代码示例

Python 代码

from pyalink.alink import *
import pandas as pd
useLocalEnv(1)
df = pd.DataFrame([
    ["1:3,2:4,4:7", 1],
    ["1:3,2:NaN", 3],
    ["2:4,4:5", 4]
])
data = BatchOperator.fromDataframe(df, schemaStr="vec string, id bigint")
vecFill = VectorImputerTrainBatchOp().setSelectedCol("vec")
model = data.link(vecFill)
VectorImputerPredictBatchOp().setOutputCol("vec1").linkFrom(model, data).print()

Java 代码

import org.apache.flink.types.Row;
import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.dataproc.vector.VectorImputerPredictBatchOp;
import com.alibaba.alink.operator.batch.dataproc.vector.VectorImputerTrainBatchOp;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import org.junit.Test;
import java.util.Arrays;
import java.util.List;
public class VectorImputerPredictBatchOpTest {
    @Test
    public void testVectorImputerPredictBatchOp() throws Exception {
        List <Row> df = Arrays.asList(
            Row.of("1:3,2:4,4:7", 1),
            Row.of("1:3,2:NaN", 3),
            Row.of("2:4,4:5", 4)
        );
        BatchOperator <?> data = new MemSourceBatchOp(df, "vec string, id int");
        BatchOperator <?> vecFill = new VectorImputerTrainBatchOp().setSelectedCol("vec");
        BatchOperator <?> model = data.link(vecFill);
        new VectorImputerPredictBatchOp().setOutputCol("vec1").linkFrom(model, data).print();
    }
}

运行结果

| vec | id | vec1 | | —- | —- | —- |

| 1:3,2:4,4:7 | 1 | 1:3.0 2:4.0 4:7.0 |

| 1:3,2:NaN | 3 | 1:3.0 2:4.0 |

| 2:4,4:5 | 4 | 2:4.0 4:5.0 |