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,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)
| File | Size | Uploaded | |
|---|---|---|---|
| woe-0.1.4.tar.gz | 1.0 MB | Details |
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| 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 |
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Release files / woe-0.1.4-py3-none-any.whl
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| Size | 19.8 kB |
| Tags | Python 3 |
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Release files / woe-0.1.4-py2-none-any.whl
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| Size | 19.8 kB |
| Tags | Python 2 |
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