LambdaMart | LambdaMart python implementation | Build Tool library

by discobot Python Version: Current License: No License

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

kandi X-RAY | LambdaMart Summary

LambdaMart is a Python library typically used in Utilities, Build Tool, Numpy applications. LambdaMart has no bugs, it has no vulnerabilities and it has low support. However LambdaMart build file is not available. You can download it from GitHub.

LambdaMart python implementation

Support

Quality

Security

License

Reuse

Support

LambdaMart has a low active ecosystem.

It has 63 star(s) with 39 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 1 have been closed. On average issues are closed in 517 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of LambdaMart is current.

Quality

LambdaMart has 0 bugs and 0 code smells.

Security

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

LambdaMart code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

LambdaMart 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

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

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

LambdaMart saves you 60 person hours of effort in developing the same functionality from scratch.

It has 157 lines of code, 16 functions and 1 files.

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

Top functions reviewed by kandi - BETA

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

Train the model .
Query the KL divergence of a single page .
Calculate the DCG of a given page .
Evaluate the given model .
Compute the k - score score of a prediction .
Groups by score .
Compute the lambdas for a prediction .
Evaluate the model .
Compute the DCG of a point .
Calculate the DCG .

Get all kandi verified functions for this library.

LambdaMart Key Features

No Key Features are available at this moment for LambdaMart.

LambdaMart Examples and Code Snippets

No Code Snippets are available at this moment for LambdaMart.

Community Discussions

Trending Discussions on LambdaMart

What metrics can I use to validate and test RankNet in the RankLib library in the Lemur Project?

QUESTION

What metrics can I use to validate and test RankNet in the RankLib library in the Lemur Project?

Asked 2018-Mar-28 at 03:17

I am currently using the RankLib implementation of the RankNet algorithm (-ranker 4) with a held-out set. I am using the jar file in terminal to run this.

The documentation stipulates:

metric2t (e.g. NDCG, ERR, etc) only applies to list-wise algorithms (AdaRank, Coordinate Ascent and LambdaMART). Point-wise and pair-wise techniques (MART, RankNet, RankBoost), due to their nature, always use their internal RMSE / pair-wise loss as the optimisation criteria.

However, when I set the 'metrics2t' to ERR@10 or NDCG@10, it starts to train and validate on my chosen metric rather that 'RMSE'.

This is part of the table outputted when I run RankNet with ERR@10.

Is there something that I am missing as this seems to be a contradiction to me.

Thanks.

...

ANSWER

Answered 2018-Mar-28 at 03:17

I am not sure, but, I think even if it prints the result for those metrics, it is not optimizing for them.

The library's developers simply left it there, as for other methods it is common to use one of those metrics for validation. And there is no option to simply turn of the computing off the metrics during training.

Right now I am training a RankNet model, and it seems that ERR@10 for training and validation data is actually increasing, while the "% mis-ordered pairs" is decreasing.

Source https://stackoverflow.com/questions/43089917

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

Vulnerabilities

No vulnerabilities reported

Install LambdaMart

You can download it from GitHub.
You can use LambdaMart 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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