我正在尝试找出如何获取字段的滞后值作为数据 vector 转换步骤的一部分。
这是一个基于 dl4j 示例构建的小示例:
import org.datavec.api.records.reader.RecordReader;
import org.datavec.api.records.reader.impl.csv.CSVRecordReader;
import org.datavec.api.split.FileSplit;
import org.datavec.api.transform.TransformProcess;
import org.datavec.api.transform.schema.Schema;
import org.datavec.api.writable.Writable;
import org.datavec.local.transforms.LocalTransformExecutor;
import org.nd4j.linalg.io.ClassPathResource;
import java.io.File;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
public class myExample {
public static void main(String[] args) throws Exception {
Schema inputDataSchema = new Schema.Builder()
.addColumnString("DateTimeString")
.addColumnsString("CustomerID", "MerchantID")
.addColumnInteger("NumItemsInTransaction")
.addColumnCategorical("MerchantCountryCode", Arrays.asList("USA","CAN","FR","MX"))
.addColumnDouble("TransactionAmountUSD",0.0,null,false,false) //$0.0 or more, no maximum limit, no NaN and no Infinite values
.addColumnCategorical("FraudLabel", Arrays.asList("Fraud","Legit"))
.build();
TransformProcess tp = new TransformProcess.Builder(inputDataSchema)
.removeAllColumnsExceptFor("DateTimeString","TransactionAmountUSD")
.build();
File inputFile = new ClassPathResource("BasicDataVecExample/exampledata.csv").getFile();
//Define input reader and output writer:
RecordReader rr = new CSVRecordReader(1, ',');
rr.initialize(new FileSplit(inputFile));
//Process the data:
List<List<Writable>> originalData = new ArrayList<>();
while(rr.hasNext()){
originalData.add(rr.next());
}
List<List<Writable>> processedData = LocalTransformExecutor.execute(originalData, tp);
int numRows = 5;
System.out.println("=== BEFORE ===");
for (int i=0;i<=numRows;i++) {
System.out.println(originalData.get(i));
}
System.out.println("=== AFTER ===");
for (int i=0;i<=numRows;i++) {
System.out.println(processedData.get(i));
}
}
}
我正在寻找 TransactionAmountUSD 的滞后值(按 DateTimeString 排序)
我正在查看docs中的sequenceMovingWindowReduce但无法弄清楚。也无法真正在 examples repo 中找到任何示例这似乎做了与此类似的事情。
最佳答案
感谢 Alex Black 在 dl4j gitter channel 上的一些帮助我可以发布我自己的答案。
给 dl4j 新手的提示 - tests code 中有很多好东西值得一看。除了示例和教程之外，还有。
这是我更新的玩具示例代码:
package org.datavec.transform.basic;
import org.datavec.api.records.reader.RecordReader;
import org.datavec.api.records.reader.impl.csv.CSVRecordReader;
import org.datavec.api.split.FileSplit;
import org.datavec.api.transform.TransformProcess;
import org.datavec.api.transform.schema.Schema;
import org.datavec.api.transform.sequence.comparator.NumericalColumnComparator;
import org.datavec.api.transform.transform.sequence.SequenceOffsetTransform;
import org.datavec.api.writable.Writable;
import org.datavec.local.transforms.LocalTransformExecutor;
import org.joda.time.DateTimeZone;
import org.nd4j.linalg.io.ClassPathResource;
import java.io.File;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
public class myExample {
public static void main(String[] args) throws Exception {
Schema inputDataSchema = new Schema.Builder()
.addColumnString("DateTimeString")
.addColumnsString("CustomerID", "MerchantID")
.addColumnInteger("NumItemsInTransaction")
.addColumnCategorical("MerchantCountryCode", Arrays.asList("USA","CAN","FR","MX"))
.addColumnDouble("TransactionAmountUSD",0.0,null,false,false) //$0.0 or more, no maximum limit, no NaN and no Infinite values
.addColumnCategorical("FraudLabel", Arrays.asList("Fraud","Legit"))
.build();
TransformProcess tp = new TransformProcess.Builder(inputDataSchema)
.removeAllColumnsExceptFor("CustomerID", "DateTimeString","TransactionAmountUSD")
.stringToTimeTransform("DateTimeString","YYYY-MM-DD HH:mm:ss.SSS", DateTimeZone.UTC)
.convertToSequence(Arrays.asList("CustomerID"), new NumericalColumnComparator("DateTimeString"))
.offsetSequence(Arrays.asList("TransactionAmountUSD"),1, SequenceOffsetTransform.OperationType.NewColumn)
.build();
File inputFile = new ClassPathResource("BasicDataVecExample/exampledata.csv").getFile();
//Define input reader and output writer:
RecordReader rr = new CSVRecordReader(0, ',');
rr.initialize(new FileSplit(inputFile));
//Process the data:
List<List<Writable>> originalData = new ArrayList<>();
while(rr.hasNext()){
originalData.add(rr.next());
}
List<List<List<Writable>>> processedData = LocalTransformExecutor.executeToSequence(originalData, tp);
System.out.println("=== BEFORE ===");
for (int i=0;i<originalData.size();i++) {
System.out.println(originalData.get(i));
}
System.out.println("=== AFTER ===");
for (int i=0;i<processedData.size();i++) {
System.out.println(processedData.get(i));
}
}
}
这应该会给出如下所示的输出，您可以在其中看到添加了每个客户 ID 的交易金额的最后一个值的现在列。
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m\fasterxml\jackson\core\jackson-annotations\2.5.1\jackson-annotations-2.5.1.jar;C:\Users\amaguire\.m2\repository\javax\servlet\javax.servlet-api\3.1.0\javax.servlet-api-3.1.0.jar;C:\Users\amaguire\.m2\repository\org\apache\commons\commons-compress\1.16.1\commons-compress-1.16.1.jar;C:\Users\amaguire\.m2\repository\org\apache\commons\commons-math3\3.5\commons-math3-3.5.jar;C:\Users\amaguire\.m2\repository\org\apache\curator\curator-recipes\2.8.0\curator-recipes-2.8.0.jar;C:\Users\amaguire\.m2\repository\org\apache\curator\curator-framework\2.8.0\curator-framework-2.8.0.jar;C:\Users\amaguire\.m2\repository\org\apache\curator\curator-client\2.8.0\curator-client-2.8.0.jar;C:\Users\amaguire\.m2\repository\org\apache\zookeeper\zookeeper\3.4.6\zookeeper-3.4.6.jar;C:\Users\amaguire\.m2\repository\jline\jline\0.9.94\jline-0.9.94.jar;C:\Users\amaguire\.m2\repository\com\typesafe\config\1.3.0\config-1.3.0.jar;C:\Users\amaguire\.m2\repository\org\datavec\datavec-hadoop\1.0.0-beta3\datavec-hadoop-1.0.0-beta3.jar;C:\Users\amaguire\.m2\repository\org\datavec\datavec-local\1.0.0-beta3\datavec-local-1.0.0-beta3.jar;C:\Users\amaguire\.m2\repository\com\codepoetics\protonpack\1.15\protonpack-1.15.jar;C:\Users\amaguire\.m2\repository\org\datavec\datavec-arrow\1.0.0-beta3\datavec-arrow-1.0.0-beta3.jar;C:\Users\amaguire\.m2\repository\org\nd4j\nd4j-arrow\1.0.0-beta3\nd4j-arrow-1.0.0-beta3.jar;C:\Users\amaguire\.m2\repository\com\fasterxml\jackson\dataformat\jackson-dataformat-yaml\2.6.5\jackson-dataformat-yaml-2.6.5.jar;C:\Users\amaguire\.m2\repository\com\fasterxml\jackson\dataformat\jackson-dataformat-xml\2.6.5\jackson-dataformat-xml-2.6.5.jar;C:\Users\amaguire\.m2\repository\com\fasterxml\jackson\module\jackson-module-jaxb-annotations\2.6.5\jackson-module-jaxb-annotations-2.6.5.jar;C:\Users\amaguire\.m2\repository\com\fasterxml\jackson\datatype\jackson-datatype-joda\2.6.5\jackson-datatype-joda-2.6.5.jar;C:\Users\amaguire\.m2\repository\com\carrotsearch\hppc\0.8.1\hppc-0.8.1.jar;C:\Users\amaguire\.m2\repository\org\apache\arrow\arrow-vector\0.11.0\arrow-vector-0.11.0.jar;C:\Users\amaguire\.m2\repository\io\netty\netty-buffer\4.1.22.Final\netty-buffer-4.1.22.Final.jar;C:\Users\amaguire\.m2\repository\io\netty\netty-common\4.1.22.Final\netty-common-4.1.22.Final.jar;C:\Users\amaguire\.m2\repository\org\apache\arrow\arrow-memory\0.11.0\arrow-memory-0.11.0.jar;C:\Users\amaguire\.m2\repository\org\apache\arrow\arrow-format\0.11.0\arrow-format-0.11.0.jar" org.datavec.transform.basic.myExample
log4j:WARN No appenders could be found for logger (io.netty.util.internal.logging.InternalLoggerFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
=== BEFORE ===
[2016-01-01 17:00:00.000, 830a7u3, u323fy8902, 1, USA, 100.00, Legit]
[2016-01-01 18:03:01.256, 830a7u3, 9732498oeu, 3, FR, 73.20, Legit]
[2016-01-03 02:53:32.231, 78ueoau32, w234e989, 1, USA, 1621.00, Fraud]
[2016-01-03 09:30:16.832, t842uocd, 9732498oeu, 4, USA, 43.19, Legit]
[2016-01-04 23:01:52.920, t842uocd, cza8873bm, 10, MX, 159.65, Legit]
[2016-01-05 02:28:10.648, t842uocd, fgcq9803, 6, CAN, 26.33, Fraud]
[2016-01-05 10:15:36.483, rgc707ke3, tn342v7, 2, USA, -0.90, Legit]
=== AFTER ===
[[1451948512920, t842uocd, 159.65, 43.19], [1451960890648, t842uocd, 26.33, 159.65]]
[[1451671381256, 830a7u3, 73.20, 100.00]]
[]
[]
Process finished with exit code 0
关于java - 使用 Datavec 变换滞后值，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/56045519/