TrainSequentialClassifier operation

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Warning

This documentation refers to the Classic QDK, which has been replaced by the Modern QDK.

Please see https://aka.ms/qdk.api for the API documentation for the Modern QDK.

Namespace: Microsoft.Quantum.MachineLearning

Package: Microsoft.Quantum.MachineLearning

Given the structure of a sequential classifier, trains the classifier on a given labeled training set.

operation TrainSequentialClassifier (models : Microsoft.Quantum.MachineLearning.SequentialModel[], samples : Microsoft.Quantum.MachineLearning.LabeledSample[], options : Microsoft.Quantum.MachineLearning.TrainingOptions, trainingSchedule : Microsoft.Quantum.MachineLearning.SamplingSchedule, validationSchedule : Microsoft.Quantum.MachineLearning.SamplingSchedule) : (Microsoft.Quantum.MachineLearning.SequentialModel, Int)

Input

models : SequentialModel[]

An array of models to be used as starting points during training.

samples : LabeledSample[]

A set of labeled training data that will be used to perform training.

options : TrainingOptions

Configuration to be used when training; see TrainingOptions user defined type and DefaultTrainingOptions function for more details.

trainingSchedule : SamplingSchedule

A sampling schedule to use when selecting samples from the training data during training steps.

validationSchedule : SamplingSchedule

A sampling schedule to use when selecting samples from the training data when selecting which start point resulted in the best classifier score.

Output : (SequentialModel,Int)

  • A parameterization of the given classifier and a bias between the two classes, together corresponding to the best result from each of the given start points.
  • The number of misses observed at the best classifier model.

See Also