FuzzyLogicRecommenderSystem | Complete Java Approach

by arajajyothibabu Java Version: Current License: No License

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

kandi X-RAY | FuzzyLogicRecommenderSystem Summary

FuzzyLogicRecommenderSystem is a Java library. FuzzyLogicRecommenderSystem has no bugs, it has no vulnerabilities and it has low support. However FuzzyLogicRecommenderSystem build file is not available. You can download it from GitHub.

Java EE Project with JSPs.

Support

Quality

Security

License

Reuse

Support

FuzzyLogicRecommenderSystem has a low active ecosystem.

It has 6 star(s) with 4 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of FuzzyLogicRecommenderSystem is current.

Quality

FuzzyLogicRecommenderSystem has 0 bugs and 0 code smells.

Security

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

FuzzyLogicRecommenderSystem code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

FuzzyLogicRecommenderSystem 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

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

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

FuzzyLogicRecommenderSystem saves you 1703 person hours of effort in developing the same functionality from scratch.

It has 3774 lines of code, 209 functions and 63 files.

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

Top functions reviewed by kandi - BETA

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

Returns the difference between the two users
Creates the IN IN SQL statement
Select the distance metric
Get all users
Calculates the difference between two movies
Get the set of genres for a specific movie id
Convert a SQL object to an int array
Get the average genres of a movie
Calculates the difference between two users
Returns the average rating of a user
Get the ratings for a user
Calculates the acceptance rate for a movie
Get the list of movies rated by the user
Get the similar movies
Get processed movies list
Retrieves the list of movies from the database
Calculates the difference between two users vs users
Calculates the difference between users
Compare if the movie is the same
Determines the difference between two movies
Returns a hashCode instance for the movie
Calculates the difference between two movies
Sorts a map by its distinguished name
Sorts the movies in a Map
Returns the dissimilarity between two users
Gets the genres for the given set of genres

Get all kandi verified functions for this library.

FuzzyLogicRecommenderSystem Key Features

No Key Features are available at this moment for FuzzyLogicRecommenderSystem.

FuzzyLogicRecommenderSystem Examples and Code Snippets

No Code Snippets are available at this moment for FuzzyLogicRecommenderSystem.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install FuzzyLogicRecommenderSystem

You can download it from GitHub.
You can use FuzzyLogicRecommenderSystem 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 FuzzyLogicRecommenderSystem 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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