推荐负采样 (NegativeItemSamplingBatchOp)

Java 类名：com.alibaba.alink.operator.batch.recommendation.NegativeItemSamplingBatchOp

Python 类名：NegativeItemSamplingBatchOp

功能介绍

当给定user-item pair数据的时候，为数据生成若干负样本数据，构成训练数据。

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
samplingFactor	采样因子	采样因子	Integer			3

代码示例

Python 代码

from pyalink.alink import *

import pandas as pd

useLocalEnv(1)

df_data = pd.DataFrame([
     [1, 1],
     [2, 2],
     [2, 3],
     [4, 1],
     [4, 2],
     [4, 3],
])

data = BatchOperator.fromDataframe(df_data, schemaStr='user bigint, item bigint')

NegativeItemSamplingBatchOp().linkFrom(data).print()

Java 代码

import org.apache.flink.types.Row;

import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.recommendation.NegativeItemSamplingBatchOp;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import org.junit.Test;

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

public class NegativeItemSamplingBatchOpTest {
	@Test
	public void testNegativeItemSamplingBatchOp() throws Exception {
		List <Row> df_data = Arrays.asList(
			Row.of(1, 1),
			Row.of(2, 2),
			Row.of(2, 3),
			Row.of(4, 1),
			Row.of(4, 2),
			Row.of(4, 3)
		);
		BatchOperator <?> data = new MemSourceBatchOp(df_data, "user int, item int");
		new NegativeItemSamplingBatchOp().linkFrom(data).print();
	}
}

运行结果

user	item	label
2	1	0
1	3	0
4	1	1
4	2	1
1	3	0
2	1	0
2	1	0
4	3	1
2	2	1
2	3	1
2	1	0
1	1	1
2	1	0
1	3	0
2	1	0