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Security-Scenes-Feature-Engineering-Toolkit, Continuous Integration.

Project description

# FXY:*Security-Scenes-Feature-Engineering-Toolkit*

[![](https://img.shields.io/badge/python-3.7-red)](https://www.python.org/) [![](https://img.shields.io/github/license/404notf0und/fxy)](https://github.com/404notf0und/FXY/blob/master/LICENSE) [![](https://img.shields.io/badge/Support%20Security%20Scenes-7%2B-green)](https://github.com/404notf0und/FXY/tree/master/data) [![](https://img.shields.io/badge/Feature%20Methods-3%2B-yellow)](https://github.com/404notf0und/FXY/blob/master/feature_vec/nlp2vec.py) [![](https://img.shields.io/github/stars/404notf0und/FXY)](https://github.com/404notf0und/FXY/stargazers)

[中文文档](https://github.com/404notf0und/FXY/blob/master/CN-README.md)

FXY is an open-sourced feature engineering framework for data preprocessing, feature engineering, model training and testing in multiple security scenes.

# Features

  • Supports the feature engineering of multiple security scenarios

  • Built-in multiple universal feature engineering methods

  • Built-in multiple deep learning models

  • Pipline jobs

# Requirements

  • Python3.7

  • Pip

# Installation

git clone https://github.com/404notf0und/FXY

pip install -r requirement.txt

# Usage

from feature_vec.nlp2vec import tfidf,wordindex,word2vec nlp=word2vec(one_class=False,tunning=True,punctuation=’concise’) fx1,fy1=nlp.fit_transform(x1,y1) fx2=nlp.transform(x2)

# Documentation

# How to Contribute

  1. Check for open issues or open a fresh issue to start a discussion around a feature idea or a bug

  2. Email me [root@4o4notfound.org](root@4o4notfound.org)

  3. Welcome to submit Feature-Engineering scripts,The method you contributed will be made public.

# Other

# Contact

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