Py Hyperpy 0.0.5 | GitLocker.com Product

Description:

pyhyperpy 0.0.5

hyperpy
HyperPy: An automatic hyperparameter optimization framework

Description

HyperPy: Library for automatic hyperparameter optimization. Build on top of Optuna to perform hyperparameter optimization with low code.
This library corresponds to part of the work of Sergio A. Mora Pardo
ðŸ‘¶ Our current version:
Installation

You can install hyperpy with pip:
# pip install py-hyperpy

Example
Import the library:
import hyperpy as hy
from hyperpy import ExampleConfig # Just for example

Reading data:
data=ExampleConfig()
train, test, sub = data.readData()

Extract features:
feat_X = train.filter(['Pclass','Age', 'SibSp', 'Parch','Fare']).values
Y = train.Survived.values

Run the optimization:
running=hy.run(feat_X, Y)
study = running.buildStudy()

See the results:
print("best params: ", study.best_params)
print("best test accuracy: ", study.best_value)
best_params, best_value = hy.results.results(study)

NOTE
The function hy.run() return a Study object. And only needs: Features, target. In the example: best test accuracy = 0.7407407164573669
Documentation
Documentation is available at hyperpy
Working on tutorial, meanwhile explore documentation.
Development
Source code is available at hyperpy
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