Package adams.data.tabnet

Class TabularRegression

java.lang.Object

adams.data.tabnet.TabularRegression

public final class TabularRegression
extends Object

Method Summary

Modifier and Type	Method	Description
static ai.djl.nn.Block	createBlock(ai.djl.zero.Performance performance, int featureSize, int labelSize)
static ai.djl.repository.zoo.ZooModel<ai.djl.basicdataset.tabular.ListFeatures,Float>	train(ai.djl.basicdataset.tabular.TabularDataset dataset, ai.djl.zero.Performance performance)	Trains a Model on a custom dataset.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

createBlock

public static ai.djl.nn.Block createBlock(ai.djl.zero.Performance performance,
                                          int featureSize,
                                          int labelSize)

train

public static ai.djl.repository.zoo.ZooModel<ai.djl.basicdataset.tabular.ListFeatures,Float> train(ai.djl.basicdataset.tabular.TabularDataset dataset,
                                                                                                         ai.djl.zero.Performance performance)
                                                                                                  throws IOException,
                                                                                                         ai.djl.translate.TranslateException

Trains a Model on a custom dataset. Currently, trains a TabNet Model.

In order to train on a custom dataset, you must create a custom TabularDataset to load your data.

Parameters:

dataset - the data to train with

performance - to determine the desired model tradeoffs

Returns:

the model as a ZooModel

Throws:

IOException - if the dataset could not be loaded

ai.djl.translate.TranslateException - if the translator has errors