Credit Scoring - IESEG School of Management
Project description
Credit Scoring Module Class: 2022 & 2023 |
Overview
-
Odds based Grouping (OBG)
-
OBGEncoder
pred_var
: Name of predictor variable. Values can be either continuous or categorical.target_var
: Name of binary target variable.
.fit
df
: DataFrame containing pred_var and target_var.max_delta
: max difference between odds for merging two levels. default: 0.05min_bins
: minimum number of bins. default: 3q
: number of quantiles when converting continuous variable to categorical. default: 10
.transform
df
: Transform pred_var based on fitted bins.
.fit_transform
df
: DataFrame containing pred_var and target_var. Transform pred_var based on fitted bins.
fit_dict: dictionary containing the matched category levels and fitted bins.
lookup: dictionary containing cutoff values for continuous variable (empty if pred_var is categorical).
-
-
Weight of Evidence (WOE)
-
WOEEncoder
pred_var
: Name of predictor variable.Values can be either continuous or categorical.target_var
: Name of binary target variable.target_value
: Value indicating event. default: 1.
.fit
df
: DataFrame containing pred_var and target_var.stop_limit
: Stops WOE based merging of the predictor's classes/levels in case the resulting information value (IV) decreases more than (e.g. 0.05 = 5%) compared to the preceding binning step. stop_limit=0 will skip any WOE based merging. Increasing the stop_limit will simplify the binning solution and may avoid overfitting. Accepted value range: 0 to 0.5. default: 0.1.q
: number of quantiles when converting continuous variable to categorical. default: 10
.transform
df
: Transform pred_var based on fitted bins
.fit_transform
df
: DataFrame containing pred_var and target_var. Transform pred_var based on fitted bins.
.test_limit
df
: DataFrame containing pred_var and target_var to test stop limits at 1%, 2.5%, 5% and 10%.
fit_dict: dictionary containing the matched category levels and fitted bins.
lookup: dictionary containing cutoff values for continuous variable (empty if pred_var is categorical).
-
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
ieseg_credscore-0.23.6.tar.gz
(12.0 kB
view hashes)