Metadata-Version: 2.1
Name: mljar-supervised
Version: 0.3.4
Summary: Automated Machine Learning for Supervised tasks
Home-page: https://github.com/mljar/mljar-supervised
Author: MLJAR, Inc.
Author-email: contact@mljar.com
License: MIT
Description: # mljar-supervised
        
        [![Build Status](https://travis-ci.org/mljar/mljar-supervised.svg?branch=master)](https://travis-ci.org/mljar/mljar-supervised)
        [![PyPI version](https://badge.fury.io/py/mljar-supervised.svg)](https://badge.fury.io/py/mljar-supervised)
        [![PyPI pyversions](https://img.shields.io/pypi/pyversions/mljar-supervised.svg)](https://pypi.python.org/pypi/mljar-supervised/)
        
        
        ## Automated Machine Learning 
        
        `mljar-supervised` is Automated Machine Learning package. It can train ML models for:
        
        - binary classification,
        - multi-class classification,
        - regression.
        
        ## Quick example
        
        There is simple interface available with `fit` and `predict` methods.
        
        ```python
        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)
        ```
        
        For details please check [AutoML API Docs](docs/api.md).
        
        ## Installation
        
        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
        ```
        
        
        
Keywords: automl,machine learning,random forest,keras,xgboost,lightgbm,catboost
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
