multibayes | Multiclass Naive Bayesian Classification | Machine Learning library

by lytics Go Version: Current License: No License

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kandi X-RAY | multibayes Summary

multibayes is a Go library typically used in Artificial Intelligence, Machine Learning applications. multibayes has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Multiclass naive Bayesian document classification. Often in document classification, a document may have more than one relevant classification — a question on [stackoverflow] might have tags "go", "map", and "interface". While multinomial Bayesian classification offers a one-of-many classification, multibayes offers tools for many-of-many classification. The multibayes library strives to offer efficient storage and calculation of multiple Bayesian posterior classification probabilities.

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Support

multibayes has a low active ecosystem.

It has 74 star(s) with 8 fork(s). There are 27 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 2 have been closed. On average issues are closed in 0 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of multibayes is current.

Quality

multibayes has 0 bugs and 0 code smells.

Security

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

multibayes code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

multibayes 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

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

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

It has 605 lines of code, 32 functions and 12 files.

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

Top functions reviewed by kandi - BETA

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

Poster returns a map of predictions for the classifier .
BayesRule returns the probability of the given probabilities .
decodeNGram converts a string to a ngram structure
NewClassifier creates a new Classifier .
returns the number of elements in array2
NewClassifierFromJSON creates a Classifier from JSON
Validate the tokenizer configuration .
LoadClassifierFromFile loads a Classifier from a file .
newSparseMatrix returns a new sparseMatrix .
max returns the maximum of two integers .

Get all kandi verified functions for this library.

multibayes Key Features

No Key Features are available at this moment for multibayes.

multibayes Examples and Code Snippets

No Code Snippets are available at this moment for multibayes.

Community Discussions

Trending Discussions on multibayes

Can I use the Rcpp code in R without installing Rtools?

QUESTION

Can I use the Rcpp code in R without installing Rtools?

Asked 2018-Aug-10 at 09:04

The Window HPC server in my lab does not have Rtools, so I've got this message when I sourced the Rcpp code.

...

ANSWER

Answered 2018-Aug-09 at 03:01

Briefly:

The narrow answer is that "yes, in theory you get by without Rtools" if you happened to install binary-identical version (including patches) of gcc et al. In practice, you cannot (on Windows).
An easy way around is to compile a package of your code outside of the HPC server and deploy the binary build of that package on it. Easy. And no Rtools needed for binaries!
If you do HPC you may also want to look into Linux.

Source https://stackoverflow.com/questions/51758096

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

Vulnerabilities

No vulnerabilities reported

Install multibayes

You can download it from GitHub.

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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