woe 0.1.4

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

woe

version: 0.1.4

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

Installation

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

$ pip install woe

or installing from git

$ 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 module function tree

|- __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()
|   |-- proc_cor_eval()
|   |-- proc_validation()
|   |-- 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()
|   |-- process_train_woe()
|   |-- process_woe_trans()
|   |-- search()
|   |-- woe_trans()
|- ftrl.py
|   |-- FTRL()
|   |-- LR()
|- GridSearch.py
|   |-- fit_single_lr()
|   |-- grid_search_lr_c()
|   |-- grid_search_lr_c_main()
|   |-- grid_search_lr_validation()

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 0.1.4 2018-03-01

• support py3

woe 0.1.3 2018-02-09

• woe.feature_process.proc_woe_discrete(): fix bug when deal with discrete varibales

• woe.eval.eval_feature_detail(): fix bug : utf-8 output file format

• woe.GridSearch.grid_search_lr_c_main(): add function warper for convenience and high efficiency

• woe.GridSearch.grid_search_lr_c_validation(): monitor the ks performance of training sets and test sets on different ‘c’

• supplement examples test scripts

woe 0.1.2 2017-12-05

• woe.ftrl.FTRL(): add online learning module

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,[e-mail].