OneVsOneLearningTInput, TBinary, TModel Methods

Sets a callback function that takes a set of parameters and creates a learning algorithm for learning each of the binary inner classifiers needed by the one-vs-rest classification strategy. Calling this method sets the Learner property.

Sets a callback function that takes a set of parameters and creates a learning algorithm for learning each of the binary inner classifiers needed by the one-vs-rest classification strategy. Calling this method sets the Learner property.

Creates an instance of the model to be learned. Inheritors of this abstract class must define this method so new models can be created from the training data.

Determines whether the specified object is equal to the current object.

Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.

Serves as the default hash function.

Gets the Type of the current instance.

Learns a model that can map the given inputs to the given outputs.

Creates a shallow copy of the current Object.

Raises the [E:SubproblemFinished] event.

Raises the [E:SubproblemStarted] event.

Returns a string that represents the current object.

Checks whether an object implements a method with the given name.

Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.

Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.

Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.