ETIP-Project | element tagging problem for Chinese insurance policy

by ETIP-team Python Version: Current License: No License

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

kandi X-RAY | ETIP-Project Summary

ETIP-Project is a Python library. ETIP-Project has no bugs, it has no vulnerabilities and it has low support. However ETIP-Project build file is not available. You can download it from GitHub.

-1. CNN-SW ：source code. A method for Nested NER by sliding window. -2. Database ：500 Chinese insurance contracts, which include life, disability, health, property, home, and auto insurance. ETIP dataset is a kind of nested NER, but different from GENIA and ACE2005, in particular the length of the entities. -3. TOI-CNN : Text of Interst CNN.

Support

Quality

Security

License

Reuse

Support

ETIP-Project has a low active ecosystem.

It has 11 star(s) with 4 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

ETIP-Project has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of ETIP-Project is current.

Quality

ETIP-Project has no bugs reported.

Security

ETIP-Project has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

ETIP-Project does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

ETIP-Project releases are not available. You will need to build from source code and install.

ETIP-Project has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

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

Run test
Convert a region to a bounding box
R Compute the non - maximum suppression
Compute a counts dataframe from a confusion matrix
Denormalize a bounding box
Loads the training data from a pickle file
Calculate the feature scaling
Transform two bounding boxes
Calculate the overlap area of two arrays
Find the positions of the word in the cut list
Count words by neg
Reads the train data
Return the path to the model dir
Convert a list of words to word vectors
Returns the path to the write result
Create the training path for the given index
Prints the arguments of the optimizer
Return the path to the write result
Train k - fold model
Creates a batch of training examples
Convert words to features
Evaluate ground truth test
Prepare data
Process the ground truth test data
Start training
Given a confusion matrix return a pandas dataframe of counts
Detect file and write to file

Get all kandi verified functions for this library.

ETIP-Project Key Features

No Key Features are available at this moment for ETIP-Project.

ETIP-Project Examples and Code Snippets

No Code Snippets are available at this moment for ETIP-Project.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install ETIP-Project

You can download it from GitHub.
You can use ETIP-Project 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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