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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

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

Project details


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