RNN-HA | offical website | Machine Learning library

by tzzcl Python Version: Current License: No License

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

kandi X-RAY | RNN-HA Summary

RNN-HA is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. RNN-HA has no bugs, it has no vulnerabilities and it has low support. However RNN-HA build file is not available. You can download it from GitHub.

This is the offical website for the implementation of RNN-HA. This package is developed by Mr. Chen-Lin Zhang (and Dr. Xiu-Shen Wei (If you have any problem about the code, please feel free to contact Mr. Chen-Lin Zhang (zhangcl@lamda.nju.edu.cn). The package is free for academic usage. You can run it at your own risk. For other purposes, please contact Dr. Xiu-Shen Wei (weixs.gm@gmail.com).

Support

Quality

Security

License

Reuse

Support

RNN-HA has a low active ecosystem.

It has 30 star(s) with 8 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 3 have been closed. On average issues are closed in 8 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of RNN-HA is current.

Quality

RNN-HA has 0 bugs and 0 code smells.

Security

RNN-HA has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

RNN-HA code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

RNN-HA 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

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

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

RNN-HA saves you 371 person hours of effort in developing the same functionality from scratch.

It has 886 lines of code, 54 functions and 9 files.

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

Top functions reviewed by kandi - BETA

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

Compute the forward function
Perform forward preparation
Load the VGG model
Backward computation
Forward computation

Get all kandi verified functions for this library.

RNN-HA Key Features

No Key Features are available at this moment for RNN-HA.

RNN-HA Examples and Code Snippets

No Code Snippets are available at this moment for RNN-HA.

Community Discussions

Trending Discussions on RNN-HA

What do input layers represent in a Hierarchical Attention Network

in-group time-to event counter

QUESTION

What do input layers represent in a Hierarchical Attention Network

Asked 2019-Apr-07 at 17:32

I'm trying to grasp the idea of a Hierarchical Attention Network (HAN), most of the code i find online is more or less similar to the one here: https://medium.com/jatana/report-on-text-classification-using-cnn-rnn-han-f0e887214d5f :

...

ANSWER

Answered 2019-Apr-06 at 12:12

The HAN model processes the text in a hierarchy: it takes a document already splitted into sentences (that's why the shape of input2 is (MAX_SENTS,MAX_SENT_LENGTH)); then it processes each sentence independently using sentEncoder model (that's why the shape of input1 is (MAX_SENT_LENGTH,)), and finally it processes all the encoded sentences together.

So in your code the whole model is stored in model and its input layer is input2 which you would fed with documents which have been splitted into sentences and their words have been integer encoded (to make it compatible with the embedding layer). The other input layer belongs to the sentEncoder model which is used inside the model (and not directly by you):

Source https://stackoverflow.com/questions/55545866

QUESTION

in-group time-to event counter

Asked 2017-Jul-11 at 15:08

I'm trying to work through the methodology for churn prediction I found here:

Let's say today is 1/6/2017. I have a pandas dataframe, df, that I want to add two columns to.

...

ANSWER

Answered 2017-Jun-21 at 01:12

To get the days until the next event, we can add a column that backfills the date of the next event:

Source https://stackoverflow.com/questions/44662267

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

Vulnerabilities

No vulnerabilities reported

Install RNN-HA

You can download it from GitHub.
You can use RNN-HA 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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