Metadata-Version: 2.1
Name: random-brain
Version: 0.1.2
Summary: Python Random Brain Module
Home-page: https://github.com/einelson/Random-brain
Author: Ethan Nelson
Author-email: ethanisaacnelson@gmail.com
License: UNKNOWN
Description: # Random-brain
        
        [![](https://img.shields.io/badge/Python-3776AB?style=for-the-badge&logo=python&logoColor=white)](https://www.python.org/)
        
        
        [![](https://img.shields.io/badge/Maintained%3F-yes-green.svg)]()
        [![](https://img.shields.io/website-up-down-green-red/http/monip.org.svg)](https://einelson.github.io/projects/random_brain/random_brain.html)
        [![](https://img.shields.io/bitbucket/issues/einelson/Random-brain)]()
        
        
        ## About
        Random brain is the neural network implementation of a random forest. Its purpose is to combine the strengths of multiple nerual networks.
        
        ## Background on random forests
        A random forest is a machine learning model that is composed of multiple decision trees. These trees in the forest all predict an outcome and the majority rules.
        
        ## Similarities
        Just as the random forest is a vote based ML algorithm, the random brain is a vote based algorithm as well, but uses neural networks specified by the user rather than decision forests.
        
        ## Setting up Random brain
        ```
        pip install random-brain
        ```
        
        ## API
        Init the brain module and class.
        ```
        from random_brain import random_brain
        brain = random_brain.random_brain()
        ```
        
        **import models()**
        
        Import models will take in a directory or a single .h5 file. Sub directories will be ignored.
        ```
        brain.import_models(model_path = 'path/to/model.h5')
        brain.import_models(model_path = 'path/to/directory')
        ```
        
        **show_brain()**
        
        Shows the keys used in the brain. This should just be the name of each imported model
        ```
        brain.show_brain()
        ```
        
        
        **clear_brain()**
        
        Clear a single model or more by entering in the model name as a list. Leave blank to clear all models.
        ```
        brain.clear_brain(item_list = ['model to remove'])
        ```
        
        **vote**
        
        Add in yTest to cast votes. Vote() will only return the votes as a numpy array and not actual predictions. This is useful if you want to run your own statistics on the votes.
        
        ```
        brain.vote(yTest = [1, 2, 3, 4, ...])
        ```
        
        **predict (in development)**
        
        Add in your yTest to make predictions. This will attempt to make a prediction based off of the networks and will return a single answer. This is still in development.
        
        In the future prediction and threading options will be added and improved.
        ```
        brain.predict(yTest = [1, 2, 3, 4, ...])
        ```
        
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
