Fast Auto Machine Learning
Project description
fastautoml
fastautoml
is powerful and computationally efficient Python library for automated machine learning, intended for data scientists and with the goal of maximize their productivity.
Prerequisites
fastautoml
requires:
- scikit-learn (>= 0.22)
- pandas (>= 0.25)
User Installation
If you already have a working installation of scikit-learn
and pandas
, the easiest way to install fastautoml
is using pip
:
pip install fastautoml
Running
The following example shows how to compute an optimal model for the MNIST dataset included with scikit-learn
.
from fastautoml.fastautoml import AutoClassifier
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
X, y = load_digits(return_X_y=True)
X_train, X_test, y_train, y_test = train_test_split(X, y)
model = AutoClassifier()
model.fit(X_train, y_train)
print("Score:", model.score(X_test, y_test))
Help
- User Guide
- Reference API (TBD)
- Examples of usage
Authors
R. Leiva and contributors. If you want to contribute to this project, please contact with the main author.
License
This project is licensed under the 3-Clause BSD license - see the LICENSE.md file for details.
Aknowledgements
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 732667 RECAP
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