NRLMFb | rescored Neighborhood Regularized Logistic Matrix

by akiyamalab Python Version: Current License: GPL-2.0

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

kandi X-RAY | NRLMFb Summary

NRLMFb is a Python library typically used in Institutions, Learning, Education applications. NRLMFb has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However NRLMFb build file is not available. You can download it from GitHub.

NRLMFβ: Bata-distribution-rescored Neighborhood Regularized Logistic Matrix Factorization for Improving Performance of Drug–Target Interaction Prediction

Support

Quality

Security

License

Reuse

Support

NRLMFb has a low active ecosystem.

It has 8 star(s) with 1 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

NRLMFb has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of NRLMFb is current.

Quality

NRLMFb has 0 bugs and 0 code smells.

Security

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

NRLMFb code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

NRLMFb is licensed under the GPL-2.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

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

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

Installation instructions are not available. Examples and code snippets are available.

It has 1777 lines of code, 96 functions and 16 files.

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

Top functions reviewed by kandi - BETA

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

Evaluate the NRLF using a method
Rescore polynomial
Constructs the neighborhood of the given drug
Calculate the evaluation of a drug
Evaluate the NRLF CVF
Computes mean confidence interval
Train the model
Evaluate a nrlF function
Builds the neighborhood of the drug
Calculates the evaluation of a test
Run nrlmf
Retrieve the list of drugs and targets
Read parameters from file
Gets cross validation data
Performs fixations on the model
Evaluate the VBMF using the given method
Runs BLMNII validation
Evaluate the netLapRLS
Perform novel prediction analysis
Evaluate the CVS model
Evaluate the CVSIP model
Fix the model
Calculate the score for a test
Evaluate test
Cross validation
Evaluate nrlF function
Retrieve a list of drugs and target names

Get all kandi verified functions for this library.

NRLMFb Key Features

No Key Features are available at this moment for NRLMFb.

NRLMFb Examples and Code Snippets

No Code Snippets are available at this moment for NRLMFb.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install NRLMFb

You can download it from GitHub.
You can use NRLMFb 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

These scripts was implemented by Tomohiro Ban. E-mail: ban@bi.c.titech.ac.jp. Department of Computer Science, School of Computing, Tokyo Institute of Technology, Japan http://www.bi.cs.titech.ac.jp/. If you have any questions, please feel free to contact the author.

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