ALINK(二十九)：特征工程（八）特征组合与交叉（三）Hash Cross特征 (HashCrossFeatureBatchOp)

Hash Cross特征 (HashCrossFeatureBatchOp)

Java 类名：com.alibaba.alink.operator.batch.feature.HashCrossFeatureBatchOp

Python 类名：HashCrossFeatureBatchOp

功能介绍

哈希特征列组合算法能够将选定的离散列组合成单列的向量类型的数据。

参数说明

名称	中文名称	描述	类型	是否必须？	默认值
outputCol	输出结果列列名	输出结果列列名，必选	String	✓
selectedCols	选择的列名	计算列对应的列名列表	String[]	✓
numFeatures	向量维度	生成向量长度	Integer		262144
reservedCols	算法保留列名	算法保留列	String[]		null

代码示例

Python 代码

from pyalink.alink import *
import pandas as pd
useLocalEnv(1)
df = pd.DataFrame([
    ["1.0", "1.0", 1.0, 1],
    ["1.0", "1.0", 0.0, 1],
    ["1.0", "0.0", 1.0, 1],
    ["1.0", "0.0", 1.0, 1],
    ["2.0", "3.0", None, 0],
    ["2.0", "3.0", 1.0, 0],
    ["0.0", "1.0", 2.0, 0],
    ["0.0", "1.0", 1.0, 0]])
data = BatchOperator.fromDataframe(df, schemaStr="f0 string, f1 string, f2 double, label bigint")
cross = HashCrossFeatureBatchOp().setSelectedCols(['f0', 'f1', 'f2']).setOutputCol('cross').setNumFeatures(4)
print(cross.linkFrom(data))

Java 代码

import org.apache.flink.types.Row;
import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.feature.HashCrossFeatureBatchOp;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import org.junit.Test;
import java.util.Arrays;
import java.util.List;
public class HashCrossFeatureBatchOpTest {
  @Test
  public void testHashCrossFeatureBatchOp() throws Exception {
    List <Row> df = Arrays.asList(
      Row.of("1.0", "1.0", 1.0, 1),
      Row.of("1.0", "1.0", 0.0, 1),
      Row.of("1.0", "0.0", 1.0, 1),
      Row.of("1.0", "0.0", 1.0, 1),
      Row.of("2.0", "3.0", null, 0),
      Row.of("2.0", "3.0", 1.0, 0),
      Row.of("0.0", "1.0", 2.0, 0)
    );
    BatchOperator <?> data = new MemSourceBatchOp(df, "f0 string, f1 string, f2 double, label bigint");
    BatchOperator <?> cross = new HashCrossFeatureBatchOp().setSelectedCols("f0", "f1", "f2").setOutputCol("cross")
      .setNumFeatures(4);
    System.out.print(cross.linkFrom(data));
  }
}

运行结果

f0	f1	f2	label	cross
1.0	1.0	0.0000	1	$36$33:1.0
1.0	1.0	1.0000	1	$36$15:1.0
1.0	0.0	1.0000	1	$36$33:1.0
1.0	0.0	1.0000	1	$36$33:1.0
2.0	3.0	1.0000	0	$36$20:1.0
2.0	3.0	None	0	36
0.0	1.0	1.0000	0	$36$28:1.0
0.0	1.0	2.0000	0	$36$33:1.0