Scorecard-Bundle | A High-level Scorecard Modeling API 评分卡建模尽在于此

by Lantianzz Python Version: V1.2.2 License: BSD-3-Clause

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | Scorecard-Bundle Summary

Scorecard-Bundle is a Python library typically used in Manufacturing, Utilities, Machinery, Process applications. Scorecard-Bundle has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install Scorecard-Bundle' or download it from GitHub, PyPI.

Scorecard-Bundle is a high-level Scorecard modeling API that is easy-to-use and Scikit-Learn consistent. It covers the major steps of training a Scorecard model including feature discretization with ChiMerge, WOE encoding, feature evaluation with information value and collinearity, Logistic-Regression-based Scorecard model, and model evaluation for binary classification tasks. All the transformers and model classes in Scorecard-Bundle comply with Scikit-Learn‘s fit-transform-predict convention. In Scorecard-Bundle, core algorithms in WOE/IV calculation and scorecard transformation were based on the methods introduced in Mamdouh Refaat's book '"Credit Risk Scorecards: Development and Implementation Using SAS"；ChiMerge was written based on Randy Kerber's paper "ChiMerge: Discretization of Numeric Attributes". I developed Scorecard-Bundle in my private time, but its codes wouldn't be so good if my superior Andyshi hasn't been allowing me to use it in projects at work, if my colleages (e.g. zeyunH) hasn't been active in using it, or if users didn't report issues when they found bugs. Thanks to everyone who helps to make Scorecard-Bundle better.

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Quality

Security

License

Reuse

Support

Scorecard-Bundle has a low active ecosystem.

It has 38 star(s) with 16 fork(s). There are 5 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 4 have been closed. On average issues are closed in 29 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Scorecard-Bundle is V1.2.2

Quality

Scorecard-Bundle has 0 bugs and 0 code smells.

Security

Scorecard-Bundle has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Scorecard-Bundle code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Scorecard-Bundle is licensed under the BSD-3-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Scorecard-Bundle releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed Scorecard-Bundle and discovered the below as its top functions. This is intended to give you an instant insight into Scorecard-Bundle implemented functionality, and help decide if they suit your requirements.

Predict the model
Assigns an interval base
Assign intervals to boundaries
Convert an interval to a boundary vector
Apply a scorecard to a scorecard
Plot event distribution
Return a feature distribution table
Return a pandas DataFrame of feature statistics
Fit the model
Maps an array to a list of values
Fit a logistic regression model
Return a list of important features that have a given threshold
Return the feature important features that are important
Return the top features of the top features
Apply fit to features
Transform the features into a numpy array

Get all kandi verified functions for this library.

Scorecard-Bundle Key Features

No Key Features are available at this moment for Scorecard-Bundle.

Scorecard-Bundle Examples and Code Snippets

No Code Snippets are available at this moment for Scorecard-Bundle.

Community Discussions

No Community Discussions are available at this moment for Scorecard-Bundle.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Scorecard-Bundle

Installing the latest version is strongly recommended as every version either corrected known bugs or added useful functionality. In principle, critical bugs are fixed as soon as they are revealed. Therefore please file an issue if you suspect the presence of a bug when using Scorecard-Bundle. Note that Scorecard-Bundle depends on NumPy, Pandas, matplotlib, Scikit-Learn, and SciPy, which can be installed individually or together through Anaconda.
Pip: Scorecard-Bundle can be installed with pip: pip install --upgrade scorecardbundle ！Note that the latest version may be not available at some pip mirror site (e.g. https://mirrors.aliyun.com/pypi/simple/). Therefore in order to update to the latest version, use the following command to specify the source as https://pypi.org/project pip install -i https://pypi.org/project --upgrade scorecardbundle
Manually: Download codes from github <https://github.com/Lantianzz/Scorecard-Bundle> and import them directly: import sys sys.path.append('E:\Github\Scorecard-Bundle') # add path that contains the codes from scorecardbundle.feature_discretization import ChiMerge as cm from scorecardbundle.feature_discretization import FeatureIntervalAdjustment as fia from scorecardbundle.feature_encoding import WOE as woe from scorecardbundle.feature_selection import FeatureSelection as fs from scorecardbundle.model_training import LogisticRegressionScoreCard as lrsc from scorecardbundle.model_evaluation import ModelEvaluation as me from scorecardbundle.model_interpretation import ScorecardExplainer as mise

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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