omikuji | efficient implementation of Partitioned Label Trees

by tomtung Rust Version: 0.5.1 License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions Vulnerabilities Install Support

kandi X-RAY | omikuji Summary

omikuji is a Rust library. omikuji has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

An efficient implementation of Partitioned Label Trees (Prabhu et al., 2018) and its variations for extreme multi-label classification, written in Rust with love.

Support

Quality

Security

License

Reuse

Support

omikuji has a low active ecosystem.

It has 63 star(s) with 8 fork(s). There are 3 watchers for this library.

There were 1 major release(s) in the last 12 months.

There are 3 open issues and 18 have been closed. On average issues are closed in 13 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of omikuji is 0.5.1

Quality

omikuji has no bugs reported.

Security

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

License

omikuji 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

omikuji releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of omikuji

Get all kandi verified functions for this library.

omikuji Key Features

No Key Features are available at this moment for omikuji.

omikuji Examples and Code Snippets

Omikuji,Usage

Rust

Lines of Code : 157

License : Permissive (MIT)

Copy

$ omikuji train --help
Train a new omikuji model

USAGE:
    omikuji train [OPTIONS] 

ARGS:
    
            Path to training dataset file

            The dataset file is expected to be in the format of the Extreme Classification
            Reposi

Omikuji,Build & Install,Python Binding

Rust

Lines of Code : 27

License : Permissive (MIT)

Copy

pip install omikuji

pip install git+https://github.com/tomtung/omikuji.git -v

import omikuji

# Train
hyper_param = omikuji.Model.default_hyper_param()
# Adjust hyper-parameters as needed
hyper_param.n_trees = 5
model = omikuji.Model.train_on_data(

Omikuji,Build & Install

Rust

Lines of Code : 4

License : Permissive (MIT)

Copy

cargo install omikuji --features cli

cargo install --git https://github.com/tomtung/omikuji.git --features cli

omikuji train eurlex_train.txt --model_path ./model
omikuji test ./model eurlex_test.txt --out_path predictions.txt

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install omikuji

Omikuji can be easily built & installed with Cargo as a CLI app:.

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: