Regression Problem

Justin · July 10, 2022, 9:22am

I am study Quickstart with Deeplearning4J. This is classfier example, but I change to linear regression. My target is to predict a number, may be this number not in my dataset lables.
By the example,

RecordReaderDataSetIterator trainIterator = new RecordReaderDataSetIterator.Builder(trainRecordReader, batchSize)
.classification(finalSchema.getIndexOfColumn(“Exited”), 2)
.build();

I change to

RecordReaderDataSetIterator trainIterator = new RecordReaderDataSetIterator.Builder(trainRecordReader, batchSize).regression(finalSchema.getIndexOfColumn(“LABEL_STD”))
.build();

and

MultiLayerConfiguration config = new NeuralNetConfiguration.Builder()
.seed(0xC0FFEE)
.weightInit(WeightInit.XAVIER)
.activation(Activation.TANH)
.updater(new Adam.Builder().learningRate(0.001).build())
.l2(0.000316)
.list(
new DenseLayer.Builder().nOut(finalSchema.numColumns() - 1).build(),
new DenseLayer.Builder().nOut(finalSchema.numColumns() - 1).build(),
new DenseLayer.Builder().nOut(finalSchema.numColumns() - 1).build(),
new DenseLayer.Builder().nOut(finalSchema.numColumns() - 1).build(),
new DenseLayer.Builder().nOut(finalSchema.numColumns() - 1).build(),
new RnnOutputLayer.Builder(LossFunctions.LossFunction.MSE).nOut(1).activation(Activation.IDENTITY).build())
.setInputType(InputType.feedForward(finalSchema.numColumns() - 1))
.build();

but i got the following error

[vert.x-eventloop-thread-0] INFO org.deeplearning4j.ui.VertxUIServer - Deeplearning4j UI server started at: http://localhost:9000
[main] INFO org.deeplearning4j.ui.VertxUIServer - StatsStorage instance attached to UI: InMemoryStatsStorage(uid=206f2af3)
Exception in thread “main” java.lang.IllegalStateException: Expected rank 3 labels array, got label array with shape [80, 1]
at org.nd4j.common.base.Preconditions.throwStateEx(Preconditions.java:639)
at org.nd4j.common.base.Preconditions.checkState(Preconditions.java:301)
at org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer.backpropGradient(RnnOutputLayer.java:58)
at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.calcBackpropGradients(MultiLayerNetwork.java:1984)
at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore(MultiLayerNetwork.java:2799)
at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore(MultiLayerNetwork.java:2742)
at org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(BaseOptimizer.java:174)
at org.deeplearning4j.optimize.solvers.StochasticGradientDescent.optimize(StochasticGradientDescent.java:61)
at org.deeplearning4j.optimize.Solver.optimize(Solver.java:52)
at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fitHelper(MultiLayerNetwork.java:2343)
at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(MultiLayerNetwork.java:2301)
at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(MultiLayerNetwork.java:2364)
at com.jufan.machinelearning.trainer.JoblogTrainer.AnalysisAndTraining(JoblogTrainer.java:189)
at com.jufan.machinelearning.trainer.JoblogTrainer.main(JoblogTrainer.java:50)

how and i solve it.

Thanks a lot.

agibsonccc · July 11, 2022, 8:19am

@Justin you need to use a sequence record reader for training RNNs. This is classification but should give you a starting point: deeplearning4j-examples/Conv1DUCISequenceClassification.java at 60de3144b7619a6c80fab899baac9301df1a882d · eclipse/deeplearning4j-examples · GitHub

Justin · July 12, 2022, 9:56am

@agibsonccc Thank you.
have any example to predictor a number, not classify.

agibsonccc · July 12, 2022, 10:17am

@Justin I’m aware of that. My point was showing you how to use the input data. Use some of that example as your base for that.
Beyond that,you just need to tell the iterator that you have a regression problem and what column it is. See more here: https://deeplearning4j.konduit.ai/v/en-1.0.0-m1.1/deeplearning4j/reference/computation-graph#example-1-regression-data-recordreadermultidatasetiterator

Justin · July 12, 2022, 2:54pm

@agibsonccc Thank you for your kind explanation.

following is my column

TransformProcess transformProcess = new TransformProcess.Builder(schema)
.removeColumns(“ECM01”, “ECM03”, “SHB02”, “SHB021”, “SHB03”, “SHB031”, “ECM45”, “SHBCONF”, “SFB22”, “SFB221”, “SHB04”, “SFB05”,“SFB06”,“SHB10”)
.categoricalToOneHot(“ECM04”)
.categoricalToOneHot(“PRDTYPE”)//PRDTYPE
.categoricalToOneHot(“SPL”)//SPL
.categoricalToOneHot(“SPEC1”) //SPEC1
.categoricalToOneHot(“SPL”) //ACTIONTYPE
.normalize(“BORE”, Normalize.MinMax, analysis)//BORE
.normalize(“STROKE”, Normalize.MinMax, analysis)//STROKE
.categoricalToOneHot(“APPLYPRD”)//APPLYPRD
.normalize(“SHB111”, Normalize.MinMax, analysis)
.normalize(“SHB033”, Normalize.MinMax, analysis)
.normalize(“LABEL_COST”, Normalize.MinMax, analysis)
.normalize(“LABEL_STD”, Normalize.MinMax, analysis)
.build();

following , trainIterator, is my iterator:

Schema finalSchema = transformProcess.getFinalSchema();
TransformProcessRecordReader trainRecordReader = new TransformProcessRecordReader(new CSVRecordReader(), transformProcess);
trainRecordReader.initialize(inputSplit);
int batchSize = 80;
RecordReaderDataSetIterator trainIterator = new RecordReaderDataSetIterator.Builder(trainRecordReader, batchSize)
.regression(finalSchema.getIndexOfColumn(“LABEL_STD”))
.build();

my problem is , train a model to predictor “LABEL_STD”

agibsonccc · July 13, 2022, 4:18am

@Justin I kept telling you multiple times you need to use the sequence record reader for this not the normal one. Please take the time to read and understand what I told you.

If you don’t do that then I can assume you’re ignoring what I wrote and unfortunately that means helping you is a waste of time.

If it is because english is not your first language or some other issue please notify me of that and I can try to clarify things for you.

Justin · July 13, 2022, 2:43pm

@agibsonccc English is not your first language. Thank your help.
I would try “sequence record reader”
Thank you.

Justin · July 13, 2022, 3:04pm

@agibsonccc Thank your telling multiple times to use the sequence record reader. and time to time reading your suggestion. By the key work “sequence record reader” and my tangle about TransformProcess.
I find a good example

github.com

PacktPublishing/Java-Deep-Learning-Cookbook/blob/master/02_Data_Extraction_Transform_and_Loading/sourceCode/cookbook-app/src/main/java/com/javadeeplearningcookbook/app/recordreaderexamples/SequenceRecordReaderExample.java

package com.javadeeplearningcookbook.app.recordreaderexamples;

import org.datavec.api.records.reader.SequenceRecordReader;
import org.datavec.api.records.reader.impl.csv.CSVSequenceRecordReader;
import org.datavec.api.records.reader.impl.transform.TransformProcessSequenceRecordReader;
import org.datavec.api.split.NumberedFileInputSplit;
import org.datavec.api.transform.TransformProcess;
import org.datavec.api.transform.schema.Schema;
import org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator;
import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;

import java.io.File;
import java.io.IOException;
import java.util.Arrays;

public class SequenceRecordReaderExample {

    public static void main(String[] args){
        try {
            SequenceRecordReader trainFeatures = new CSVSequenceRecordReader(1);

This file has been truncated. show original

may be good for me.

agibsonccc · July 14, 2022, 10:04am

@Justin thanks for engaging with me. That’s a much better indicator of where you are at. Now I get what you are doing. Please use the TransformProcessSequenceRecordReader for your use case: deeplearning4j/TransformProcessSequenceRecordReader.java at master · eclipse/deeplearning4j · GitHub

Justin · July 15, 2022, 8:02am

@agibsonccc Thanks for your kind suggestion

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