mljar-supervised
is Automated Machine Learning package. It can train ML models for:
- binary classification,
- multi-class classification,
- regression.
There is simple interface available with fit
and predict
methods.
import pandas as pd
from supervised.automl import AutoML
df = pd.read_csv("https://raw.githubusercontent.com/pplonski/datasets-for-start/master/adult/data.csv", skipinitialspace=True)
X = df[df.columns[:-1]]
y = df["income"]
automl = AutoML()
automl.fit(X, y)
predictions = automl.predict(X)
From source code:
git clone https://github.com/mljar/mljar-supervised.git
cd mljar-supervised
python setup.py install
From PyPi repository (PyPi can be not updated, it is better to install from source):
pip install mljar-supervised
Installation for development
git clone https://github.com/mljar/mljar-supervised.git
virtualenv venv --python=python3.6
source venv/bin/activate
pip install -r requirements.txt
pip install -r requirements_dev.txt