Statistical IV: Statistical Hypothesis Testing for the Information Value (IV). Evaluation of the predictive power of features using the IV with specific thresholds for each dataset.
Project description
Statistical IV
Optimize your machine learning models with 'Statistical-IV'. Perform automated feature selection based on statistics and customize error control.
-
Import package
from statistical_iv import api
-
Provide a DataFrame as Input:
- Supply a DataFrame
df
containing your data for IV calculation.
- Supply a DataFrame
-
Specify Predictor Variables:
- Prived a list of predictor variable names (
variables_names
) to analyze.
- Prived a list of predictor variable names (
-
Define the Target Variable:
- Specify the name of the target variable (
var_y
) in your DataFrame.
- Specify the name of the target variable (
-
Indicate Variable Types:
- Define the type of your predictor variables as 'categorical' or 'numerical' using the
type_vars
parameter.
- Define the type of your predictor variables as 'categorical' or 'numerical' using the
-
Optional: Set Maximum Bins:
- Adjust the maximum number of bins for discretization (optional) using the
max_bins
parameter.
- Adjust the maximum number of bins for discretization (optional) using the
-
Call the
statistical_iv
Function:- Calculate Statistical IV information by calling the
statistical_iv
function from api with the specified parameters (That is used for OptimalBinning package).
result_df = api.statistical_iv(df, variables_names, var_y, type_vars, max_bins)
- Calculate Statistical IV information by calling the
Example Result:
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
statistical_iv-0.3.0.tar.gz
(5.1 kB
view hashes)
Built Distribution
Close
Hashes for statistical_iv-0.3.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 733113ab0beacbe22ba9bb5e2aca53cde2ea0c4b4b3fe71b0e603f9e94c80cb6 |
|
MD5 | 4353ddf1c9cbb80b6a741571e89e4073 |
|
BLAKE2b-256 | 3afa726616e444dde95cb70986e1958541c1663f9c22ec7d482e8047997acc35 |