RankLib | A Learning to Rank Library | Awesome List library

by jattenberg Java Version: Current License: Non-SPDX

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

kandi X-RAY | RankLib Summary

RankLib is a Java library typically used in Awesome, Awesome List applications. RankLib has no bugs, it has no vulnerabilities and it has low support. However RankLib build file is not available and it has a Non-SPDX License. You can download it from GitHub.

A Learning to Rank Library. Copied from:

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Quality

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License

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Support

RankLib has a low active ecosystem.

It has 130 star(s) with 63 fork(s). There are 18 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 1364 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of RankLib is current.

Quality

RankLib has 0 bugs and 0 code smells.

Security

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

RankLib code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

RankLib has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

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

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

Main program
Prepare the feature description file
Read a feature file
Evaluates the current ranking algorithm using the defined features
Performs training
Calculates the Euclidean distance between two vectors
Shuffles the list of features
Initialize the training data
Reorder the score
Train training data
Read feature file
Load the ranking
Calculates the mean of the given rank
Load ideal deviations from a file
Estimate the Loss loss
Gunzip an input file
Initialize the network
Replaces the changes in an RRList with the same rank
Learned training
Entry point for the rank algorithm
Swaps the changes in a ranked list
Loads the network from a file
Package - private for testing
Returns the number of relevant changes in a rank list
Train the scorer
Load the network

Get all kandi verified functions for this library.

RankLib Key Features

No Key Features are available at this moment for RankLib.

RankLib Examples and Code Snippets

No Code Snippets are available at this moment for RankLib.

Community Discussions

Trending Discussions on RankLib

How to get the feature importance of ranklib generated random forests model?

QUESTION

How to get the feature importance of ranklib generated random forests model?

Asked 2021-Feb-21 at 21:07

Using ranklib's learning to rank random forests generates an xml-like model. Ranklib has a tool that provides features' frequency which cannot necessarily be considered as feature importance.

How can I get the Gini feature importance or Gini index of random forests generated by ranklib? How to parse the tree generated?

Found in the Sourceforge discussion forum that you need to parse the model file yourself.

...

ANSWER

Answered 2021-Feb-19 at 04:47

I, personally, had a lot of struggles to get the Gini importance of features from a ranklib random forest and finally succeeded. Here I share the Github repository I made to solve the problem.

You can do it by running this command (use python3):

python Gini.py

Please see the repository for more details on how to do it.

Source https://stackoverflow.com/questions/66271935

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

Vulnerabilities

No vulnerabilities reported

Install RankLib

You can download it from GitHub.
You can use RankLib like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the RankLib component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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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