Metadata-Version: 2.0
Name: woe
Version: 0.1.2
Summary: Tools for WoE Transformation mostly used in ScoreCard Model for credit rating
Home-page: https://github.com/boredbird/woe
Author: boredbird
Author-email: 1002937942@qq.com
License: MIT
Keywords: math,finance,scorecard,woe,iv
Platform: all
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: Implementation
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Software Development :: Libraries
Requires-Dist: matplotlib (>=2.0.0)
Requires-Dist: numpy (>=1.11.3)
Requires-Dist: pandas (>=0.19.2)
Requires-Dist: scipy (>=0.18.1)

woe
==========

.. image:: https://travis-ci.org/justdoit0823/pywxclient.svg?branch=master
    :target: https://travis-ci.org/justdoit0823/pywxclient

version: 0.1.2

Tools for WoE Transformation mostly used in ScoreCard Model for credit rating

Installation
--------------------------------

We can simply use pip to install, as the following:

.. code-block:: bash

   $ pip install woe

or installing from git

.. code-block:: bash

   $ pip install git+https://github.com/boredbird/woe


Features
========

  * Split tree with IV criterion

  * Rich and plentiful model eval methods

  * Unified format and easy for output

  * Storage of IV tree for follow-up use


**woe aims to only support Python 2.7, so there is no guarantee for Python 3.**

**woe** module function tree
============

.. code-block:: bash
	|- __init__
	|- config.py 
	|   |-- config
	|   	|-- __init__
	|		|-- change_config_var_dtype()
	|		|-- load_file()
	|- eval.py 
	|   |-- compute_ks()
	|   |-- eval_data_summary()
	|   |-- eval_feature_detail()
	|   |-- eval_feature_stability()
	|   |-- eval_feature_summary()
	|   |-- eval_model_stability()
	|   |-- eval_model_summary()
	|   |-- eval_segment_metrics()
	|   |-- plot_ks()
	|   |-- wald_test()
	|- feature_process.py 
	|   |-- binning_data_split()
	|   |-- calculate_iv_split()
	|   |-- calulate_iv()
	|   |-- change_feature_dtype()
	|   |-- check_point()
	|   |-- fillna()
	|   |-- format_iv_split()
	|   |-- proc_woe_continuous()
	|   |-- proc_woe_discrete()
	|   |-- search()
	|   |-- woe_trans()
	|- GridSearch.py 
	|   |-- grid_search_lr_c()

Examples
========

In the examples directory, there is a simple woe transformation program as tutorials.

Or you can write a more complex program with this `woe` package.

Version Records
================

woe 0.1.1 2017-11-28

	* woe.config.load_file(): change param data_path to be optional
	* woe.eval.eval_feature_stability(): fix bug : psi_dict['stability_index'] computation error
	* woe.feature_process.change_feature_dtype(): add friendly tips when encounter a error
	* woe.feature_process.calulate_iv(): refactor the code
	* woe.feature_process.calculate_iv_split(): refactor the code
	* woe.feature_process.binning_data_split(): reduce the number of len() function calls with __len__() and shape attributes;replace namedtuple with dict
	* woe.feature_process.fillna(): new added function to fill null value
	* woe.GridSearch.grid_search_lr_c(): list of regularization parameter c specified inside the function is changed to the user specified

woe 0.0.9 2017-11-21

	* Add module : GridSearch for the search of optimal hyper parametric C in LogisticRegression
	* Code refactoring: function compute_ks and plot_ks

woe 0.0.8 2017-09-28

	* More flexible: cancel conditional restriction in function feature_process.change_feature_dtype() 
	* Fix bug: the wrong use of deepcopy in function feature_process.woe_trans()

woe 0.0.7 2017-09-19

	* Fix bug: eval.eval_feature_detail raises ValueError('arrays must all be same length')
	* Add parameter interface: alpha specified step learning rate ,default 0.01

How to Contribute
--------------------------------

Email me,1002937942@qq.com.


