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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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