version: 0.1.8
Tools for WoE Transformation mostly used in ScoreCard Model for credit rating
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
- 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
|- __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()
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.
- 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
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