Displaying 1 to 20 from 21 results

natural - general natural language facilities for node

  •    Javascript

"Natural" is a general natural language facility for nodejs. Tokenizing, stemming, classification, phonetics, tf-idf, WordNet, string similarity, and some inflections are currently supported.

bayes - Naive-Bayes Classifier for node.js

  •    Javascript

bayes takes a document (piece of text), and tells you what category that document belongs to. Returns an instance of a Naive-Bayes Classifier.

Spell Corrector

  •    DotNet

A spell corrector that uses Bayes algorithm and BK (Burkhard-Keller) tree.

simple_bayes - A Naive Bayes machine learning implementation in Elixir.

  •    Elixir

A Naive Bayes machine learning implementation in Elixir. In machine learning, naive Bayes classifiers are a family of simple probabilistic classifiers based on applying Bayes' theorem with strong (naive) independence assumptions between the features.


  •    Javascript

A collection of low-level machine learning algorithms for node.js.This project is quite new and documentation will be on the way shortly. In the meantime you can check out the spec folder for examples of how to use the algorithms.

stemmer - An English (Porter2) stemming implementation in Elixir.

  •    Elixir

An English (Porter2) stemming implementation in Elixir. The Stemmer.stem/1 function supports stemming a single word (String), a sentence (String) or a list of single words (List of Strings).

bayesian-bandit.js - Bayesian bandit implementation for Node and the browser.

  •    Javascript

This is an adaptation of the Bayesian Bandit code from Probabilistic Programming and Bayesian Methods for Hackers, specifically d3bandits.js. The code has been rewritten to be more idiomatic and also usable as a browser script or npm package. Additionally, unit tests are included.

classify.js - Naieve Bayesian Classifier in pure javascript.

  •    Javascript

Naieve Bayesian Classifier in pure javascript. Classify.js is a Naieve Bayesian classifier for javascript applications. After training it will examples, it can classify new inputs into the groups you defined in the training set.

node-ml - A Collection of Machine Learning algorithms built for use with NodeJS

  •    Javascript

( Development is current suspended ). Models are acted upon by the perceive or predict functions. These functions currently do the same thing, the wording is indicative of the nature of the result, and the action the model has taken on the data.

Bayes - Naive Bayes Classifier in Swift for Mac and iOS

  •    Swift

Bayes is a Naive Bayes Classifier for iOS and Mac platforms. Bayes is implemented in Swift and takes advantage of generics to enable any Hashable, Equatable type of your choosing or creation for use as category or feature.

node-bayes - :chart_with_upwards_trend: Naive Bayes classifier for Node

  •    Javascript

node-bayes is a Naive Bayes classifier for Node.js. Built-in support for numeric attributes and Laplace smoothing. node-bayes © 2016+, Yos Riady. Released under the MIT License. Authored and maintained by Yos Riady with help from contributors (list).

bayes_user_input_prediction - Demonstration of using Naive Bayes to predict user inputs with Kotlin 1

  •    Kotlin

This is a simple Kotlin application that leverages Naive Bayes to categorize bank transactions. NOTE: Kotlin-Statistics now has this feature in an easy-to-use API.

bayes-classifier - Naive Bayes Classifier in JavaScript

  •    Javascript

This is a Naive Bayes classifier implementation written in JavaScript. I took out the relevant algorithms from the appratus and natural modules, and also the Porter stemmer algorithm. All credit goes to them.

BayesianTools - General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics

  •    R

New developments will be done in extra branches and will be tested before merging in the developtment branch, so the developmet version should usually be usable (consider it in a beta stage), while feature branches should be considered alpha. Windows users: the package contains c++ code, so if you compile yourself, you need RTools installed.

IncrementalInference.jl - Incremental non-parametric (and parametric) solution to factor graphs

  •    Julia

Optimization routines for incremental non-parametric and parametric solutions based on factor graphs and the Bayes (Junction) tree implemented in the Julia language (and JuliaPro). This package furthermore forms a cardinal piece of the Caesar.jl robotics toolkit, including 3D visualization and database interaction, which can serve as a base station for a robotic platform. A standalone Robot Motion Estimate package is also available.

nbayes - A Naive Bayes classifier written in JavaScript.

  •    Javascript

nbayes is a lightweight Naive Bayes Classifier written in vanilla JavaScript. It classifies a document (arbitrary piece of text) among the classes (arbitrarily named categories) it has been trained with before. This is all based on simple mathematics. As an example, you could use nbayes to answer the following questions. nbayes offers a simple and straightforward API, keeping it below 3kb (minified). It is a rewrite of ttezel/bayes and thoroughly tested.

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