Metadata-Version: 1.2
Name: toothpick-learn
Version: 0.0.1
Summary: A mini python machine library
Home-page: https://github.com/firelolix/toothpick
Author: firelolix
Author-email: shuo-ouyang@foxmail.com
License: MIT
Description-Content-Type: UNKNOWN
Description: # toothpick

        

        Toothpick is a mini "library" which contains some implementation of machine learning algorithms in Python3.6. These algorithm 

        are built on NumPy. **This "library" is just a toy**, the reason why I create it is to share my ideas and codes. 

        All algorithms have `fit` and `predict` interface like `scikit-learn`. When I implemented these algorithms, I referenced

        some books as follows: _Machine Learning_ writen by ZhiHua Zhou, _Statistical Learning Method_ writen by Hang Li and 

        _Machine Learning in Action_ writen by Peter Harrington.

        

        By the way, I am a novice in python and machine learning field, so you can put forward issues if you find some bugs or questions.

        

        ## Why named toothpick?

        

        A toothpick is a small stick of wood, plastic, bamboo, or other substance used to remove detritus from the teeth, usually

        after a meal(from wikipedia). This library is similarly small and you can "take" it after meal :P.

        

        ## How to guarantee the correctness?

        

        I compared my implementation with scikit-learn's when I was implementing these algorithms, which you can find in every single python file

        and these performance were approximate on some very simple data set.

        

        ## Algorithms implemented

        

         - Logistic Regression

         - Naive Bayes

         - K Nearest Neighbours

         - KMeans

         - Learning Vector Quantization

         - Ensemble Learning Algorithms

            - AdaBoost(only support binary classification)

            - Bagging

            - Stacking

        

        ## Todo List

        

         - Decision Tree

         - SVM

         - Regression

            - Linear Regressiong

            - Ridge Regression

            - Lasso Regression

         - Neural Network
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Python: ~=3.6
