Skip to main content

woe

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

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,1002937942@qq.com.

Metadata

Release files for woe 0.1.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for woe 0.1.4
File Size Uploaded
woe-0.1.4.tar.gz 1.0 MB Details

Built distributions (wheels)

Table of built distributions (wheels) for woe 0.1.4
File Interpreter ABI Platform
woe-0.1.4-py3-none-any.whl Python 3 none any Details
woe-0.1.4-py2-none-any.whl Python 2 none any Details

Total release size: 1.0 MB

Release files / woe-0.1.4.tar.gz

Download URL woe-0.1.4.tar.gz
Size 1.0 MB
Tags Source
SHA-256 checksum
How to use checksums
3197c09d461596b260660b7fd2bd337bd55fafb821e76953c1f3ddc45f42abaf
BLAKE2b-256 checksum
How to use checksums
eaad4cad7c22787350dbb2cd8ce3528c686ebb88e2ae9cda8c56c5e2b46f3277
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Release files / woe-0.1.4-py3-none-any.whl

Download URL woe-0.1.4-py3-none-any.whl
Size 19.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b6eecab6df49609cfcfc574bb509d30ef780d741439faf70a2bf26b64b6d8a63
BLAKE2b-256 checksum
How to use checksums
f532ba4d592dfef45338ee04ca90c37b4f3aa345bdeafcad4dcbf654ad0b14c2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Release files / woe-0.1.4-py2-none-any.whl

Download URL woe-0.1.4-py2-none-any.whl
Size 19.8 kB
Tags Python 2
SHA-256 checksum
How to use checksums
70eb7d2516d24eeed3b30b3831fd2370c2d8d528795c6a837af5d474bf868d4c
BLAKE2b-256 checksum
How to use checksums
bf269757bfb6f11706e9d9c58d511edf655823496d8f4175c951256ec2819965
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Release history Release notifications | RSS feed

This release

0.1.4 This release

3 release files

0.1.3

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.0.9

2 release files

0.0.8

2 release files

0.0.7

2 release files

0.0.6

2 release files

0.0.5

2 release files

0.0.4

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page