version: 0.1.4
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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