多热编码 (MultiHotEncoder)

举例

输入列为col_0
1. 如果没有填写discreteThresholds, 假设模型中a,b,c,d,e对应的token index为0,1,2,3,4

1.1 handleInvalid为keep

1.2 handleInvalid为skip

1.3 handleInvalid为error: 直接报错

参数说明

代码示例

Python 代码

from pyalink.alink import *

import pandas as pd

useLocalEnv(1)

df = pd.DataFrame([
    ["a b", 1],
    ["b c", 1],
    ["c d", 1],
    ["a d", 2],
    ["d e", 2],
    [None, 1]
])

inOp = BatchOperator.fromDataframe(df, schemaStr='query string, weight long')

multi_hot = MultiHotEncoder().setSelectedCols(["query"]).setOutputCols(["output"])
multi_hot.fit(inOp).transform(inOp).print()

Java 代码

import org.apache.flink.types.Row;

import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import com.alibaba.alink.pipeline.feature.MultiHotEncoder;
import org.junit.Test;

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

public class MultiHotEncoderTest {
	@Test
	public void testMultiHotEncoder() throws Exception {
		List <Row> df = Arrays.asList(
			Row.of("a b", 1),
			Row.of("b c", 1),
			Row.of("c d", 1),
			Row.of("a d", 2),
			Row.of("d e", 2),
			Row.of(null, 1)
		);
		BatchOperator <?> inOp = new MemSourceBatchOp(df, "query string, weight int");
		MultiHotEncoder multi_hot = new MultiHotEncoder().setSelectedCols("query").setOutputCols("output");
		multi_hot.fit(inOp).transform(inOp).print();
	}
}

运行结果