Java 类名:com.alibaba.alink.pipeline.dataproc.vector.VectorPolynomialExpand
Python 类名:VectorPolynomialExpand
对 Vector 进行多项式展开,组成一个新的Vector。
名称 | 中文名称 | 描述 | 类型 | 是否必须? | 取值范围 | 默认值 |
---|---|---|---|---|---|---|
selectedCol | 选中的列名 | 计算列对应的列名 | String | ✓ | ||
degree | 多项式阶数 | 多项式的阶数,默认2 | Integer | x >= 1 | 2 | |
outputCol | 输出结果列 | 输出结果列列名,可选,默认null | String | null | ||
reservedCols | 算法保留列名 | 算法保留列 | String[] | null | ||
numThreads | 组件多线程线程个数 | 组件多线程线程个数 | Integer | 1 |
from pyalink.alink import * import pandas as pd useLocalEnv(1) df = pd.DataFrame([ ["$8$1:3,2:4,4:7"], ["$8$2:4,4:5"] ]) data = BatchOperator.fromDataframe(df, schemaStr="vec string") VectorPolynomialExpand().setSelectedCol("vec").setOutputCol("vec_out").transform(data).collectToDataframe()
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.dataproc.vector.VectorPolynomialExpand; import org.junit.Test; import java.util.Arrays; import java.util.List; public class VectorPolynomialExpandTest { @Test public void testVectorPolynomialExpand() throws Exception { List <Row> df = Arrays.asList( Row.of("$8$1:3,2:4,4:7"), Row.of("$8$2:4,4:5") ); BatchOperator <?> data = new MemSourceBatchOp(df, "vec string"); new VectorPolynomialExpand().setSelectedCol("vec").setOutputCol("vec_out").transform(data).print(); } }
vec | vec_out |
---|---|
$8$1:3,2:4,4:7 | $44$2:3.0 4:9.0 5:4.0 7:12.0 8:16.0 14:7.0 16:21.0 17:28.0 19:49.0 |
$8$2:4,4:5 | $44$5:4.0 8:16.0 14:5.0 17:20.0 19:25.0 |