Feyn is a symbolic regression package named after Richard Feynman, that uses the QLattice as a simulator to generate models.
Project description
Feyn
Quick start
Feyn
is available as Python3.7+ package through pip
. You can install it with the following command:
richard@feyn:~$ pip3 install feyn
Once installed, go to your preferred Python
environment and follow along with this example.
Running a QLattice
If you're using the community edition of a QLattice
then you can instantiate it by:
import feyn
ql = feyn.QLattice()
Auto run
The quickest way to get started is to use the auto_run
function on the QLattice
. First we will make a classification problem with feyn.datasets.make_classification
.
from feyn.datasets import make_classification
train, test = make_classification()
models = ql.auto_run(train, output_name = 'y', kind = 'classification')
This returns a list of fitted models that are the best the QLattice
has sampled, sorted by ascending loss.
Evaluate
The model with the lowest loss is models[0]
. We can evaluate that model with the plot
function and it's ROC curve.
best = models[0]
best.plot(train, test)
best.plot_roc_curve(test)
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