Updating a QLattice

by: Kevin Broløs & Chris Cave
(Feyn version 3.0 or newer)

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A QLattice can be considered as a probability distribution of Model structures, that can be sampled from with the sample_model function. A structure is defined as the input names, function names and their combinations inside a Model. This excludes its weights and biases.

When you update the QLattice with a list of Models, the probability density function is updated to encourage those structures. Without updating, the QLattice will keep generating models with a random structure.

Example

Continuing from the previous sections, we now add the update function to our workflow.

import feyn
from feyn.datasets import make_classification

train, test = make_classification()

ql = feyn.QLattice()

models = ql.sample_models(train.columns, 'y', 'classification', max_complexity=10)

models = feyn.fit_models(models, train, 'binary_cross_entropy', 'bic', 4)

models = feyn.prune_models(models)

ql.update(
    models=models
)

Parameters of update

models

The list of Models to update the QLattice with.