ReliefF | Relief family of feature selection algorithms

 by   gitter-badger Python Version: Current License: MIT

X-RayKey FeaturesCode SnippetsCommunity Discussions(1)VulnerabilitiesInstallSupport

kandi X-RAY | ReliefF Summary

kandi X-RAY | ReliefF Summary

ReliefF is a Python library. ReliefF has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However ReliefF build file is not available. You can download it from GitHub.

Please check the existing open and closed issues to see if your issue has already been attended to. If it hasn't, file a new issue on this repository so we can review your issue.
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              ReliefF has a low active ecosystem.
              It has 13 star(s) with 31 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              ReliefF has no issues reported. There are 2 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of ReliefF is current.

            kandi-Quality Quality

              ReliefF has 0 bugs and 0 code smells.

            kandi-Security Security

              ReliefF has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              ReliefF code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              ReliefF is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              ReliefF releases are not available. You will need to build from source code and install.
              ReliefF has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are available. Examples and code snippets are not available.
              It has 30 lines of code, 3 functions and 3 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed ReliefF and discovered the below as its top functions. This is intended to give you an instant insight into ReliefF implemented functionality, and help decide if they suit your requirements.
            • Fits the KDTree .
            • Initialize feature scores .
            • Transform X into n features .
            Get all kandi verified functions for this library.

            ReliefF Key Features

            No Key Features are available at this moment for ReliefF.

            ReliefF Examples and Code Snippets

            No Code Snippets are available at this moment for ReliefF.

            Community Discussions

            Trending Discussions on ReliefF

            What is the fastest way to perform an exhaustive search in R

            QUESTION

            What is the fastest way to perform an exhaustive search in R
            Asked 2021-May-27 at 01:37

            I am implementing a version of the Very Large Scale Relieff algorithm detailed here.

            Simply put, Very Large Scale Relieff split the set of features N into several random subsets Ns where Ns << N. Then it calculates the Relieff weights for the features in the subset Ns. For each feature, the final weight will be the highest weight assigned among the different subsets were that particular feature appear.

            I have ~80000 features for ~100 subjects. I can calculate 10000 subsets of 8000 features each in a reasonable amount of time (~5 minutes running on 25 cores) with the following code (that is scaled down to 100 features in order to be easier to profile):

            ...

            ANSWER

            Answered 2021-May-20 at 13:38

            If I understood what you are trying to do correctly, then the answer is simpler than you think.

            Correct me if I'm wrong, but you are trying to get the max value obtained from attrEval per feature? if so, then why not just bind all results in one dataframe (or data.table), and then get the max per column like so:

            Source https://stackoverflow.com/questions/67471974

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

            Vulnerabilities

            No vulnerabilities reported

            Install ReliefF

            You can download it from GitHub.
            You can use ReliefF 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

            We welcome you to check the existing issues for bugs or enhancements to work on. If you have an idea for an extension to the ReliefF package, please file a new issue so we can discuss it.
            Find more information at:

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