向量卡方检验 (VectorChiSquareTestBatchOp)

Java 类名：com.alibaba.alink.operator.batch.statistics.VectorChiSquareTestBatchOp

Python 类名：VectorChiSquareTestBatchOp

功能介绍

针对vector数据，进行卡方检验

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
labelCol	标签列名	输入表中的标签列名	String	✓
selectedCol	选中的列名	计算列对应的列名	String	✓	所选列类型为 [DENSE_VECTOR, SPARSE_VECTOR, STRING, VECTOR]

代码示例

** 以下代码仅用于示意，可能需要修改部分代码或者配置环境后才能正常运行！**

Python 代码

无python接口

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.operator.batch.statistics.VectorChiSquareTestBatchOp;
import org.junit.Test;

import java.util.Arrays;

public class VectorChiSquareTestBatchOpTest {

	@Test
	public void testVectorChiSquareTestBatchOp() throws Exception {
		Row[] testArray = new Row[] {
			Row.of(7, "0.0  0.0  18.0  1.0", 1.0),
			Row.of(8, "0.0  1.0  12.0  0.0", 0.0),
			Row.of(9, "1.0  0.0  15.0  0.1", 0.0),
		};

		String[] colNames = new String[] {"id", "features", "clicked"};

		MemSourceBatchOp source = new MemSourceBatchOp(Arrays.asList(testArray), colNames);

		VectorChiSquareTestBatchOp test = new VectorChiSquareTestBatchOp()
			.setSelectedCol("features")
			.setLabelCol("clicked");

		test.linkFrom(source);

		test.lazyPrintChiSquareTest();

		BatchOperator.execute();
	}

}

运行结果

ChiSquareTest:

col	p	value	df
0	0.3865	0.75	1
1	0.3865	0.75	1
2	0.2231	3	2
3	0.2231	3	2