PLNetDyadRanker (jaicore-ml 0.1.3 API)

java.lang.Object
- ai.libs.jaicore.ml.dyadranking.algorithm.PLNetDyadRanker

All Implemented Interfaces:

IBatchLearner<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>, ICertaintyProvider<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>, IOnlineLearner<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>, IPredictiveModel<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>, IDyadRanker, IPLDyadRanker
```
public class PLNetDyadRanker
extends java.lang.Object
implements IPLDyadRanker, IOnlineLearner<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>, ICertaintyProvider<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>
```
A dyad ranker based on a Plackett-Luce network. All the provided algorithms are implementations of the PLModel introduced in [1]. [1] Schäfer, D., & Hüllermeier, E. (2018). Dyad ranking using Plackett--Luce models based on joint feature representations. Machine Learning, 107(5), 903–941. https://doi.org/10.1007/s10994-017-5694-9

Constructor Summary

Constructors
Constructor and Description
`PLNetDyadRanker()` Constructs a new `PLNetDyadRanker` using the default `IPLNetDyadRankerConfiguration`.
`PLNetDyadRanker(IPLNetDyadRankerConfiguration config)` Constructs a new `PLNetDyadRanker` using the given `IPLNetDyadRankerConfiguration`.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`createNetworkFromDl4jConfigFile(java.io.File configFile)` Creates a simple feed-forward `MultiLayerNetwork` using the json representation of a `MultiLayerConfiguration` in the file .
`double`	`getCertainty(IDyadRankingInstance queryInstance)` Returns the certainty for a given `IInstance`.
`IPredictiveModelConfiguration`	`getConfiguration()` Returns the `IPredictiveModelConfiguration` of this model.
`int`	`getEpoch()`
`double`	`getLogProbabilityOfTopKRanking(IDyadRankingInstance drInstance, int k)` Returns the log of the probablity of the top k of a given `IDyadRankingInstance` under the Plackett Luce model parametrized by the latent skill values predicted by the PLNet.
`double`	`getLogProbabilityOfTopRanking(IDyadRankingInstance drInstance)` Returns the the log of the probablity of the top ranking for a given `IDyadRankingInstance` under the Plackett Luce model parametrized by the latent skill values predicted by the PLNet.
`double`	`getLogProbabilityRanking(IDyadRankingInstance drInstance)` Computes the logarithmic probability for a particular ranking according to the log Placket-Luce model.
`IDyadRankingInstance`	`getPairWithLeastCertainty(IDyadRankingInstance drInstance)` Returns the pair of `Dyad`s for which the model is least certain.
`org.deeplearning4j.nn.multilayer.MultiLayerNetwork`	`getPlNet()`
`double`	`getProbabilityOfTopKRanking(IDyadRankingInstance drInstance, int k)`
`double`	`getProbabilityOfTopRanking(IDyadRankingInstance drInstance)` Returns the probablity of the top ranking for a given `IDyadRankingInstance` under the Plackett Luce model parametrized by the latent skill values predicted by the PLNet.
`double`	`getProbabilityRanking(IDyadRankingInstance drInstance)` Returns the probablity of a given `IDyadRankingInstance` under the Plackett Luce model parametrized by the latent skill values predicted by the PLNet.
`double`	`getSkillForDyad(Dyad dyad)` Returns the latent skill value predicted by the PLNet for a given `Dyad`.
`void`	`loadModelFromFile(java.lang.String filePath)` Restore a trained model from a given file path.
`java.util.List<IDyadRankingInstance>`	`predict(DyadRankingDataset dataset)` Performs multiple predictions based on the `IInstance`s contained in the given `AILabeledAttributeArrayDataset`s and returns the result.
`IDyadRankingInstance`	`predict(IDyadRankingInstance instance)` Performs a prediction based on the given `IInstance` and returns the result.
`void`	`saveModelToFile(java.lang.String filePath)` Save a trained model at a given file path.
`void`	`setConfiguration(IPredictiveModelConfiguration configuration)` Sets the `IPredictiveModelConfiguration` of this model to the given one.
`void`	`train(DyadRankingDataset dataset)` Trains this `IBatchLearner` using the given `AILabeledAttributeArrayDataset`.
`void`	`train(DyadRankingDataset dataset, int maxEpochs, double earlyStoppingTrainRatio)`
`void`	`train(java.util.List<org.nd4j.linalg.api.ndarray.INDArray> dataset)`
`void`	`train(java.util.List<org.nd4j.linalg.api.ndarray.INDArray> dataset, int maxEpochs, double earlyStoppingTrainRatio)`
`void`	`update(IDyadRankingInstance instance)` Updates this `PLNetDyadRanker` based on the given `IInstance`, which needs to be an `IDyadRankingInstance`.
`void`	`update(java.util.Set<IDyadRankingInstance> instances)` Updates this `IOnlineLearner` based on the given `Set` of `IInstance`s.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - PLNetDyadRanker
```
public PLNetDyadRanker()
```
    Constructs a new PLNetDyadRanker using the default IPLNetDyadRankerConfiguration.
  - PLNetDyadRanker
```
public PLNetDyadRanker(IPLNetDyadRankerConfiguration config)
```
    Constructs a new PLNetDyadRanker using the given IPLNetDyadRankerConfiguration.
    
    Parameters:
    
    config - Configuration for the PLNetDyadRanker.
- Method Detail
  - train
```
public void train(DyadRankingDataset dataset)
           throws TrainingException
```
    Description copied from interface: IBatchLearner
    
    Trains this IBatchLearner using the given AILabeledAttributeArrayDataset.
    
    Specified by:
    
    train in interface IBatchLearner<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>
    
    Parameters:
    
    dataset - The AILabeledAttributeArrayDataset which should be used for the training.
    
    Throws:
    
    TrainingException - If something fails during the training process.
  - train
```
public void train(java.util.List<org.nd4j.linalg.api.ndarray.INDArray> dataset)
```
  - train
```
public void train(DyadRankingDataset dataset,
                  int maxEpochs,
                  double earlyStoppingTrainRatio)
```
  - train
```
public void train(java.util.List<org.nd4j.linalg.api.ndarray.INDArray> dataset,
                  int maxEpochs,
                  double earlyStoppingTrainRatio)
```
  - update
```
public void update(IDyadRankingInstance instance)
            throws TrainingException
```
    Updates this PLNetDyadRanker based on the given IInstance, which needs to be an IDyadRankingInstance. The update procedure is based on algorithm 2 in [1].
    
    Specified by:
    
    update in interface IOnlineLearner<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>
    
    Parameters:
    
    instances - The IInstance the update should be based on. Needs to be a IDyadRankingInstance.
    
    Throws:
    
    TrainingException - If something fails during the update process.
  - update
```
public void update(java.util.Set<IDyadRankingInstance> instances)
            throws TrainingException
```
    Description copied from interface: IOnlineLearner
    
    Updates this IOnlineLearner based on the given Set of IInstances.
    
    Specified by:
    
    update in interface IOnlineLearner<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>
    
    Parameters:
    
    instances - The Set of IInstances the update should be based on.
    
    Throws:
    
    TrainingException - If something fails during the update process.
  - predict
```
public IDyadRankingInstance predict(IDyadRankingInstance instance)
                             throws PredictionException
```
    Description copied from interface: IPredictiveModel
    
    Performs a prediction based on the given IInstance and returns the result.
    
    Specified by:
    
    predict in interface IPredictiveModel<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>
    
    Parameters:
    
    instance - The IInstance for which a prediction should be made.
    
    Returns:
    
    The result of the prediction.
    
    Throws:
    
    PredictionException - If something fails during the prediction process.
  - predict
```
public java.util.List<IDyadRankingInstance> predict(DyadRankingDataset dataset)
                                             throws PredictionException
```
    Description copied from interface: IPredictiveModel
    
    Performs multiple predictions based on the IInstances contained in the given AILabeledAttributeArrayDatasets and returns the result.
    
    Specified by:
    
    predict in interface IPredictiveModel<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>
    
    Parameters:
    
    dataset - The AILabeledAttributeArrayDataset for which predictions should be made.
    
    Returns:
    
    The result of the predictions.
    
    Throws:
    
    PredictionException - If something fails during the prediction process.
  - setConfiguration
```
public void setConfiguration(IPredictiveModelConfiguration configuration)
                      throws ConfigurationException
```
    Description copied from interface: IPredictiveModel
    
    Sets the IPredictiveModelConfiguration of this model to the given one.
    
    Specified by:
    
    setConfiguration in interface IPredictiveModel<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>
    
    Throws:
    
    ConfigurationException - If something fails during the configuration process.
  - getConfiguration
```
public IPredictiveModelConfiguration getConfiguration()
```
    Description copied from interface: IPredictiveModel
    
    Returns the IPredictiveModelConfiguration of this model.
    
    Specified by:
    
    getConfiguration in interface IPredictiveModel<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>
    
    Returns:
    
    The IPredictiveModelConfiguration of this model.
  - createNetworkFromDl4jConfigFile
```
public void createNetworkFromDl4jConfigFile(java.io.File configFile)
```
    Creates a simple feed-forward MultiLayerNetwork using the json representation of a MultiLayerConfiguration in the file .
    
    Parameters:
    
    configFile - File containing the json representation of the MultiLayerConfiguration
  - saveModelToFile
```
public void saveModelToFile(java.lang.String filePath)
                     throws java.io.IOException
```
    Save a trained model at a given file path. Note that the produced file is a zip file and a ".zip" ending is added.
    
    Parameters:
    
    filePath - The file path to save to.
    
    Throws:
    
    java.io.IOException
  - loadModelFromFile
```
public void loadModelFromFile(java.lang.String filePath)
                       throws java.io.IOException
```
    Restore a trained model from a given file path. Warning: does not check whether the loaded model is a valid PLNet or conforms to the configuration of the object.
    
    Parameters:
    
    filePath - The file to load from.
    
    Throws:
    
    java.io.IOException
  - getPlNet
```
public org.deeplearning4j.nn.multilayer.MultiLayerNetwork getPlNet()
```
  - getEpoch
```
public int getEpoch()
```
  - getCertainty
```
public double getCertainty(IDyadRankingInstance queryInstance)
```
    Description copied from interface: ICertaintyProvider
    
    Returns the certainty for a given IInstance.
    
    Specified by:
    
    getCertainty in interface ICertaintyProvider<IDyadRankingInstance,IDyadRankingInstance,DyadRankingDataset>
    
    Parameters:
    
    queryInstance - IInstance for which certainty shall be obtained.
    
    Returns:
    
    Certainty of the model for the given IInstance
  - getPairWithLeastCertainty
```
public IDyadRankingInstance getPairWithLeastCertainty(IDyadRankingInstance drInstance)
```
    Returns the pair of Dyads for which the model is least certain.
    
    Parameters:
    
    drInstance - Ranking for which certainty should be assessed.
    
    Returns:
    
    The pair of Dyads for which the model is least certain.
  - getProbabilityOfTopRanking
```
public double getProbabilityOfTopRanking(IDyadRankingInstance drInstance)
```
    Returns the probablity of the top ranking for a given IDyadRankingInstance under the Plackett Luce model parametrized by the latent skill values predicted by the PLNet. This may be useful as the probability of a particular ranking diminishes drastically with increasing length of the ranking.
    
    Parameters:
    
    drInstance - IDyadRankingInstance for which the probability is computed.
    
    Returns:
    
    Probablity of the top ranking for a given IDyadRankingInstance given the Plackett Luce model parametrized by the skill values predicted by the PLNet.
  - getProbabilityOfTopKRanking
```
public double getProbabilityOfTopKRanking(IDyadRankingInstance drInstance,
                                          int k)
```
  - getLogProbabilityOfTopRanking
```
public double getLogProbabilityOfTopRanking(IDyadRankingInstance drInstance)
```
    Returns the the log of the probablity of the top ranking for a given IDyadRankingInstance under the Plackett Luce model parametrized by the latent skill values predicted by the PLNet. This may be useful as the probability of a particular ranking diminishes drastically with increasing length of the ranking.
    
    Parameters:
    
    drInstance - IDyadRankingInstance for which the probability is computed.
    
    Returns:
    
    Log of the probablity of the top ranking for a given IDyadRankingInstance given the Plackett Luce model parametrized by the skill values predicted by the PLNet.
  - getLogProbabilityOfTopKRanking
```
public double getLogProbabilityOfTopKRanking(IDyadRankingInstance drInstance,
                                             int k)
```
    Returns the log of the probablity of the top k of a given IDyadRankingInstance under the Plackett Luce model parametrized by the latent skill values predicted by the PLNet. This may be useful as the probability of a particular ranking diminishes drastically with increasing length of the ranking.
    
    Parameters:
    
    drInstance - IDyadRankingInstance for which the probability is computed.
    
    k - Number of top dyads to be considered.
    
    Returns:
    
    Log of the probablity of the top k of a the given IDyadRankingInstance given the Plackett Luce model parametrized by the skill values predicted by the PLNet.
  - getProbabilityRanking
```
public double getProbabilityRanking(IDyadRankingInstance drInstance)
```
    Returns the probablity of a given IDyadRankingInstance under the Plackett Luce model parametrized by the latent skill values predicted by the PLNet.
    
    Parameters:
    
    drInstance - IDyadRankingInstance for which the probability is computed.
    
    Returns:
    
    Probability of the given IDyadRankingInstance given the Plackett Luce model parametrized by the skill values predicted by the PLNet.
  - getLogProbabilityRanking
```
public double getLogProbabilityRanking(IDyadRankingInstance drInstance)
```
    Computes the logarithmic probability for a particular ranking according to the log Placket-Luce model.
    
    Parameters:
    
    drInstance -
    
    Returns:
    
    Logarithmic probability of the given ranking.
  - getSkillForDyad
```
public double getSkillForDyad(Dyad dyad)
```
    Returns the latent skill value predicted by the PLNet for a given Dyad.
    
    Parameters:
    
    dyad - Dyad for which the skill is to be predicted.
    
    Returns:
    
    Skill of the given Dyad.

Class PLNetDyadRanker

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

PLNetDyadRanker

PLNetDyadRanker

Method Detail

train

train

train

train

update

update

predict

predict

setConfiguration

getConfiguration

createNetworkFromDl4jConfigFile

saveModelToFile

loadModelFromFile

getPlNet

getEpoch

getCertainty

getPairWithLeastCertainty

getProbabilityOfTopRanking

getProbabilityOfTopKRanking

getLogProbabilityOfTopRanking

getLogProbabilityOfTopKRanking

getProbabilityRanking

getLogProbabilityRanking

getSkillForDyad