java-ml | Java implementations of several Machine Learning | Machine Learning library

by crm416 Java Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | java-ml Summary

java-ml is a Java library typically used in Artificial Intelligence, Machine Learning applications. java-ml has no bugs, it has no vulnerabilities and it has low support. However java-ml build file is not available. You can download it from GitHub.

A series of standard Machine Learning (classification) algorithms implemented in Java. The repository includes:. Each of these implementations satisfy the Classifier interface. Additionally, BaselineClassifier.java provides a classifier that simply predicts every example to be the most frequently occuring classification in the data set, as a point of comparison for the other implementations.

Support

Quality

Security

License

Reuse

Support

java-ml has a low active ecosystem.

It has 38 star(s) with 28 fork(s). There are 9 watchers for this library.

It had no major release in the last 6 months.

java-ml has no issues reported. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of java-ml is current.

Quality

java-ml has 0 bugs and 0 code smells.

Security

java-ml has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

java-ml code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

java-ml 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

java-ml releases are not available. You will need to build from source code and install.

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

java-ml saves you 691 person hours of effort in developing the same functionality from scratch.

It has 1598 lines of code, 89 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 java-ml and discovered the below as its top functions. This is intended to give you an instant insight into java-ml implemented functionality, and help decide if they suit your requirements.

Returns the optimal k - value k for the data set
Calculates the k nearest neighbors of the given example ex
Compute the squared distance between two vectors
Main method to test the dataset
Print out the predictions for the given classifier
Computes the error on the training examples
Predicts the label of an example
Trains the instances weights of each training instance
Get the vote count for the training examples
Performs backward elimination on the classifier
Computes the error for a labeled data set
Runs the test program
Trains the back propagation algorithm
Resets the weights of a neural network
Use forward selection
Read the next line
Open the file
Main method for testing
Get the values of the contivals
Main entry point
Calculates the error on the given dataset

Get all kandi verified functions for this library.

java-ml Key Features

No Key Features are available at this moment for java-ml.

java-ml Examples and Code Snippets

No Code Snippets are available at this moment for java-ml.

Community Discussions

Trending Discussions on java-ml

How to creat an Instance in javaml with TestData?

Unable to set the package name for classpath in randoop

QUESTION

How to creat an Instance in javaml with TestData?

Asked 2018-Sep-30 at 08:36

The small sample of my problem is in the repo.

I have the below dataset in a .data file:

...

ANSWER

Answered 2018-Sep-30 at 08:36

Well you can simply use SparseInstance method which asks for an array of Doubles. If, you convert your TestData to Double, then it will be very easy:

Source https://stackoverflow.com/questions/52543400

QUESTION

Unable to set the package name for classpath in randoop

Asked 2017-Sep-22 at 00:28

Here the project structure cloned from github after compiling on Ubuntu successfully,

...

ANSWER

Answered 2017-Jul-25 at 16:46

The error message gives you the answer:

Ignoring interface net.sf.javaml.core.Dataset specified via --classlist or --testclass. No classes to test

You are supposed to provide a class, not an interface, to the --testclass command-line argument.

By passing --testclass=net.sf.javaml.core.Dataset to Randoop, you indicated that you only want Randoop to create objects of type net.sf.javaml.core.Dataset. However, since that is an interface, it cannot be instantiated, and Randoop cannot create any objects, nor any tests.

Source https://stackoverflow.com/questions/45280294

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

Vulnerabilities

No vulnerabilities reported

Install java-ml

You can download it from GitHub.
You can use java-ml 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 java-ml 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 .