OneHotObjectiveFunction¶

class OneHotObjectiveFunction(X, y, neural_network, loss)[source]¶

An objective function for one hot encoding representation of the output. For instance, classes like [1, 0, 0], [0, 1, 0], [0, 0, 1].

Parameters:

X (ndarray) – The input data.
y (ndarray) – The target values.
neural_network (NeuralNetwork) – An instance of an quantum neural network to be used by this objective function.
loss (Loss) – A target loss function to be used in training.

Methods

gradient(weights)[source]¶

Computes gradients of this objective function given weights.

Parameters:: weights (ndarray) – an array of weights to be used in the objective function.
Returns:: Gradients of the function.
Return type:: ndarray

objective(weights)[source]¶

Computes the value of this objective function given weights.

Parameters:: weights (ndarray) – an array of weights to be used in the objective function.
Returns:: Value of the function.
Return type:: float