Metadata-Version: 1.0
Name: embayes
Version: 0.1.1
Summary: Naive Bayes classifier for embedded systems
Home-page: https://github.com/jonnor
Author: Jon Nordby
Author-email: jononor@gmail.com
License: UNKNOWN
Description: 
        # embayes
        Bayesian machine learning classifiers for embedded systems.
        Train in Python, deploy on microcontroller.
        
        ## Key features
        
        Embedded-friendly Classifier
        
        * Portable C99 code
        * No stdlib required
        * No dynamic allocations
        * Integer/fixed-point math only
        * Single header file include
        * Fast, sub-millisecond classification
        
        Convenient Training
        
        * API-compatible with [scikit-learn](http://scikit-learn.org)
        * Implemented in Python 3
        * C classifier accessible in Python using pybind11
        
        [MIT licensed](./LICENSE.md)
        
        ## Status
        **Minimally useful**
        
        * Gaussian Naive Bayes classifier implemented
        * Tested running on ESP8266 and Linux.
        * On ESP8266, 2 classes and 30 features classify in under 0.5ms
        
        ## Installing
        
        Install from git
        
            git clone https://github.com/jonnor/embayes
            python3 setup.py install --user
        
        ## Usage
        
        See [examples/cancer.py](./examples/cancer.py) and [embayes.ino](./embayes.ino)
        
        ## TODO
        
        0.2
        
        * Make estimator a wrapper around `sklearn.naivebayes.GaussianNB`
        * Make estimator work in sklearn pipeline
        * Make `pdf` approximation configurable as parameter
        
        1.0
        
        * Support generating inline C code, not needing model coefficients in RAM
        * Support de/serializing coefficients at runtime
        * Support training on microcontroller
        
Platform: UNKNOWN
