{"id":13639651,"url":"https://github.com/boredbird/woe","last_synced_at":"2025-04-19T22:33:29.769Z","repository":{"id":46104508,"uuid":"103102489","full_name":"boredbird/woe","owner":"boredbird","description":"Tools for WoE Transformation mostly used in ScoreCard Model for credit 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image:: https://travis-ci.org/justdoit0823/pywxclient.svg?branch=master\n    :target: https://travis-ci.org/justdoit0823/pywxclient\n\nversion: 0.1.4\n\nTools for WoE Transformation mostly used in ScoreCard Model for credit rating\n\nInstallation\n--------------------------------\n\nWe can simply use pip to install, as the following:\n\n.. code-block:: bash\n\n   $ pip install woe\n\nor installing from git\n\n.. code-block:: bash\n\n   $ pip install git+https://github.com/boredbird/woe\n\n\nFeatures\n========\n\n  * Split tree with IV criterion\n\n  * Rich and plentiful model eval methods\n\n  * Unified format and easy for output\n\n  * Storage of IV tree for follow-up use\n\n\n\n**woe** module function tree\n============================\n\n:: \n\n\t|- __init__\n\t|- config.py \n\t|   |-- config\n\t|   \t|-- __init__\n\t|\t\t|-- change_config_var_dtype()\n\t|\t\t|-- load_file()\n\t|- eval.py \n\t|   |-- compute_ks()\n\t|   |-- eval_data_summary()\n\t|   |-- eval_feature_detail()\n\t|   |-- eval_feature_stability()\n\t|   |-- eval_feature_summary()\n\t|   |-- eval_model_stability()\n\t|   |-- eval_model_summary()\n\t|   |-- eval_segment_metrics()\n\t|   |-- plot_ks()\n\t|   |-- proc_cor_eval()\n\t|   |-- proc_validation()\n\t|   |-- wald_test()\n\t|- feature_process.py \n\t|   |-- binning_data_split()\n\t|   |-- calculate_iv_split()\n\t|   |-- calulate_iv()\n\t|   |-- change_feature_dtype()\n\t|   |-- check_point()\n\t|   |-- fillna()\n\t|   |-- format_iv_split()\n\t|   |-- proc_woe_continuous()\n\t|   |-- proc_woe_discrete()\n\t|   |-- process_train_woe()\n\t|   |-- process_woe_trans()\n\t|   |-- search()\n\t|   |-- woe_trans()\n\t|- ftrl.py \n\t|   |-- FTRL()\n\t|   |-- LR()\n\t|- GridSearch.py \n\t|   |-- fit_single_lr()\n\t|   |-- grid_search_lr_c()\n\t|   |-- grid_search_lr_c_main()\n\t|   |-- grid_search_lr_validation()\n\n\nExamples\n========\n\nIn the examples directory, there is a simple woe transformation program as tutorials.\n\nOr you can write a more complex program with this `woe` package.\n\nVersion Records\n================\nwoe 0.1.4 2018-03-01\n\t* support py3\n\nwoe 0.1.3 2018-02-09\n\n\t* woe.feature_process.proc_woe_discrete(): fix bug when deal with discrete varibales\n\t* woe.eval.eval_feature_detail(): fix bug : utf-8 output file format\n\t* woe.GridSearch.grid_search_lr_c_main(): add function warper for convenience and high efficiency\n\t* woe.GridSearch.grid_search_lr_c_validation(): monitor the ks performance of training sets and test sets on different 'c'\n\t* supplement examples test scripts\n\n\nwoe 0.1.2 2017-12-05\n\n\t* woe.ftrl.FTRL(): add online learning module\n\nwoe 0.1.1 2017-11-28\n\n\t* woe.config.load_file(): change param data_path to be optional\n\t* woe.eval.eval_feature_stability(): fix bug : psi_dict['stability_index'] computation error\n\t* woe.feature_process.change_feature_dtype(): add friendly tips when encounter a error\n\t* woe.feature_process.calulate_iv(): refactor the code\n\t* woe.feature_process.calculate_iv_split(): refactor the code\n\t* woe.feature_process.binning_data_split(): reduce the number of len() function calls with __len__() and shape attributes;replace namedtuple with dict\n\t* woe.feature_process.fillna(): new added function to fill null value\n\t* woe.GridSearch.grid_search_lr_c(): list of regularization parameter c specified inside the function is changed to the user specified\n\t\nwoe 0.0.9 2017-11-21\n\n\t* Add module : GridSearch for the search of optimal hyper parametric C in LogisticRegression\n\t* Code refactoring: function compute_ks and plot_ks\n\nwoe 0.0.8 2017-09-28\n\n\t* More flexible: cancel conditional restriction in function feature_process.change_feature_dtype() \n\t* Fix bug: the wrong use of deepcopy in function feature_process.woe_trans()\n\t\nwoe 0.0.7 2017-09-19\n\n\t* Fix bug: eval.eval_feature_detail raises ValueError('arrays must all be same length')\n\t* Add parameter interface: alpha specified step learning rate ,default 0.01\n\nHow to Contribute\n--------------------------------\n\nEmail me,1002937942@qq.com.\n","funding_links":[],"categories":["Explaining Black Box Models and Datasets","Explainability and Fairness","Technical Resources"],"sub_categories":["Open Source/Access Responsible AI Software Packages"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fboredbird%2Fwoe","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fboredbird%2Fwoe","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fboredbird%2Fwoe/lists"}