credit-card-fraud | Analysis of credit card fraud data | Machine Learning library

by ellisvalentiner Python Version: v1.2 License: MIT

X-Ray Key Features Code Snippets(2)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | credit-card-fraud Summary

credit-card-fraud is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Keras applications. credit-card-fraud has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Analysis of credit card fraud data using neural networks.

Support

Quality

Security

License

Reuse

Support

credit-card-fraud has a low active ecosystem.

It has 59 star(s) with 27 fork(s). There are 6 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 5 have been closed. On average issues are closed in 100 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of credit-card-fraud is v1.2

Quality

credit-card-fraud has 0 bugs and 0 code smells.

Security

credit-card-fraud has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

credit-card-fraud code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

credit-card-fraud is licensed under the MIT License. This license is Permissive.

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

Reuse

credit-card-fraud releases are available to install and integrate.

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

Installation instructions are not available. Examples and code snippets are available.

credit-card-fraud saves you 30 person hours of effort in developing the same functionality from scratch.

It has 82 lines of code, 1 functions and 1 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Generate a tensorflow model .

Get all kandi verified functions for this library.

credit-card-fraud Key Features

No Key Features are available at this moment for credit-card-fraud.

credit-card-fraud Examples and Code Snippets

Credit Card Fraud Analysis,Performance

Python

Lines of Code : 10

License : Permissive (MIT)

Copy

             precision    recall  f1-score   support

        0.0       1.00      0.99      1.00    284315
        1.0       0.19      0.95      0.31       492

avg / total       1.00      0.99      1.00    284807

Predictions       0     1
Truth

Credit Card Fraud Analysis,Model

Python

Lines of Code : 1

License : Permissive (MIT)

Copy

KERAS_BACKEND=tensorflow ipython src/model.py

Community Discussions

Trending Discussions on credit-card-fraud

SVC Unable to find the attributes '_probA'

QUESTION

SVC Unable to find the attributes '_probA'

Asked 2021-Apr-20 at 14:57

I am developing credit card fraud detections project in machine learning. I have download the code form GitHub (https://github.com/devrajkataria/Credit-Card-Fraud-Detection-ML-WebApp) but I am getting following errors:

...

ANSWER

Answered 2021-Apr-20 at 14:57

This is very likely to be a versioning problem. Your scikit-learn version is probably the latest version and the model.pkl you downloaded from the repo you mentioned is an old and incompatible version.

To avoid this kind of problem, we should stick to best practices such as using a requirements.txt file defining exactly the versions using during development. The same versions could then be installed on production.

If you really need to use this model.pkl from the repo, I'd suggest creating a GitHub issue asking for a requirement.txt file. Alternatively, you could try different scikit-learn versions until you get it working, but this can be very cumbersome.

Source https://stackoverflow.com/questions/67180525

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

Vulnerabilities

No vulnerabilities reported

Install credit-card-fraud

You can download it from GitHub.
You can use credit-card-fraud like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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