Java 类名：com.alibaba.alink.operator.batch.dataproc.MultiStringIndexerTrainBatchOp
Python 类名：MultiStringIndexerTrainBatchOp

功能介绍

MultiStringIndexer 训练组件的作用是训练一个模型用于将多列字符串映射为整数，训练的时候指定多个列，每个列单独编码。
支持按照一定的次序编码。如随机、出现频次生序，出现频次降序、字符串生序、字符串降序5种方式。
设置 setStringOrderType 参数时分别对应 random frequency_asc frequency_desc alphabet_asc alphabet_desc。

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
selectedCols 选择的列名 计算列对应的列名列表 String[] ✓
stringOrderType Token排序方法 Token排序方法 String “RANDOM”, “FREQUENCY_ASC”, “FREQUENCY_DESC”, “ALPHABET_ASC”, “ALPHABET_DESC” “RANDOM”

代码示例

Python 代码

  1. from pyalink.alink import *
  3. import pandas as pd
  5. useLocalEnv(1)
  7. df = pd.DataFrame([
  8.     ["football"],
  9.     ["football"],
  10.     ["football"],
  11.     ["basketball"],
  12.     ["basketball"],
  13.     ["tennis"],
  14. ])
  17. data = BatchOperator.fromDataframe(df, schemaStr='f0 string')
  19. stringindexer = MultiStringIndexerTrainBatchOp() \
  20.     .setSelectedCols(["f0"]) \
  21.     .setStringOrderType("frequency_asc")
  23. model = stringindexer.linkFrom(data)
  24. model.print()

Java 代码

  1. import org.apache.flink.types.Row;
  3. import com.alibaba.alink.operator.batch.BatchOperator;
  4. import com.alibaba.alink.operator.batch.dataproc.MultiStringIndexerTrainBatchOp;
  5. import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
  6. import org.junit.Test;
  8. import java.util.Arrays;
  9. import java.util.List;
  11. public class MultiStringIndexerTrainBatchOpTest {
  12.     @Test
  13.     public void testMultiStringIndexerTrainBatchOp() throws Exception {
  14.         List <Row> df = Arrays.asList(
  15.             Row.of("football"),
  16.             Row.of("football"),
  17.             Row.of("football"),
  18.             Row.of("basketball"),
  19.             Row.of("basketball"),
  20.             Row.of("tennis")
  21.         );
  22.         BatchOperator <?> data = new MemSourceBatchOp(df, "f0 string");
  23.         BatchOperator <?> stringindexer = new MultiStringIndexerTrainBatchOp()
  24.             .setSelectedCols("f0")
  25.             .setStringOrderType("frequency_asc");
  26.         BatchOperator model = stringindexer.linkFrom(data);
  27.         model.print();
  28.     }
  29. }

运行结果

| column_index | token | token_index | | —- | —- | —- |

| -1 | {“selectedCols”:”[“f0”]”,”selectedColTypes”:”[“VARCHAR”]”} | null |

| 0 | tennis | 0 |

| 0 | basketball | 1 |

| 0 | football | 2 |