ProtoTree | Neural Prototype Trees for Interpretable Fine | Machine Learning library

by M-Nauta Python Version: Current License: MIT

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

kandi X-RAY | ProtoTree Summary

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

This repository presents the PyTorch code for Neural Prototype Trees (ProtoTrees). Check out our video for a short introduction!.

Support

Quality

Security

License

Reuse

Support

ProtoTree has a low active ecosystem.

It has 73 star(s) with 14 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 10 have been closed. On average issues are closed in 9 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of ProtoTree is current.

Quality

ProtoTree has 0 bugs and 0 code smells.

Security

ProtoTree has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

ProtoTree code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

ProtoTree 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

ProtoTree releases are not available. You will need to build from source code and install.

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

It has 3219 lines of code, 185 functions and 32 files.

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

Top functions reviewed by kandi - BETA

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

Run the test tree
Tensor distribution
Calculate the maximum distribution distribution of softmax distributions
Log a message to the log directory
Projects the prototypes of the trained model
Run an ensemble
Run a tree
Analyze the ensemble of the given trees
Constructs a DenseNet s features
Return the argument parser
Constructs the Denset201 features
Constructs the Densenet19 features
Constructs Densenet 121 features
Performs the forward computation
Explain a local training
Generate prediction visualization
Create a block layer
Loads VGG16 features
Loads the VGG19 model
Create a VGG16 feature model
Create a VGG_features model
Generate a VGG11 feature model
Creates a VGG_features model
Creates a VGG11 model
Create a VGG19 feature model
Construct a model of ResNet152 features

Get all kandi verified functions for this library.

ProtoTree Key Features

No Key Features are available at this moment for ProtoTree.

ProtoTree Examples and Code Snippets

No Code Snippets are available at this moment for ProtoTree.

Community Discussions

Trending Discussions on ProtoTree

what's the best way to check if one object is a prototype of another?

QUESTION

what's the best way to check if one object is a prototype of another?

Asked 2022-Jan-08 at 17:12

I believe the best way would be something like:

...

ANSWER

Answered 2022-Jan-08 at 17:12

If wouldn't be good to have that as a member method, but it's easy to implement as a standalone (recursive) function:

Source https://stackoverflow.com/questions/70634297

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

Vulnerabilities

No vulnerabilities reported

Install ProtoTree

You can download it from GitHub.
You can use ProtoTree 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 .

Find more information at: