mljar-supervised

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Automated Machine Learning

mljar-supervised is an Automated Machine Learning python package. It can train ML models for:

What's good in it?

AutoML leaderboard

The example for Decision Tree summary: Decision Tree summary

The example for LightGBM summary: Decision Tree summary

Quick example

There is a 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(results_path="directory_with_reports")
automl.fit(X, y)

predictions = automl.predict(X)

For details please check AutoML API Docs.

Examples

Installation

From PyPi repository:

pip install mljar-supervised

From source code:

git clone https://github.com/mljar/mljar-supervised.git
cd mljar-supervised
python setup.py install

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

MLJAR

The mljar-supervised is an open-source project created by MLJAR. We care about ease of use in the Machine Learning. The mljar.com provides a beautiful and simple user interface for building machine learning models.