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RMOA (version 1.1.0)

Connect R with MOA for Massive Online Analysis

Description

Connect R with MOA (Massive Online Analysis - ) to build classification models and regression models on streaming data or out-of-RAM data. Also streaming recommendation models are made available.

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Version

Install

install.packages('RMOA')

Monthly Downloads

182

Version

1.1.0

License

GPL-3

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/jwijffels/RMOA

Homepage

http://www.bnosac.be

Maintainer

Last Published

July 17th, 2022

Functions in RMOA (1.1.0)

MOA_classification_bayes

MOA bayesian classification

MOA_classification_activelearning

MOA active learning classification

MOA_classification_ensemblelearning

MOA classification using ensembles

MOA_classification_trees

MOA classification trees

Define the attributes of a dataset (factor levels, numeric or string data) in a MOA setting

datastream_matrix

data streams on a matrix

datastream_file

File data stream

MOA_recommendation_engines

MOA recommendation engines

Datastream objects and methods

trainMOA.MOA_regressor

Train a MOA regressor (e.g. a FIMTDD) on a datastream

Create a MOA classifier

Get and set options for models build with MOA.

trainMOA.MOA_recommender

Train a MOA recommender (e.g. a BRISMFPredictor) on a datastream

Create a MOA regressor

summary.MOA_regressor

Summary statistics of a MOA regressor

trainMOA.MOA_classifier

Train a MOA classifier (e.g. a HoeffdingTree) on a datastream

datastream_dataframe

data streams on a data.frame

Convert character strings to factors in a dataset

summary.MOA_recommender

Summary statistics of a MOA recommender

summary.MOA_classifier

Summary statistics of a MOA classifier

datastream_ffdf

data streams on an ffdf

Train a MOA classifier/regressor/recommendation engine on a datastream

predict.MOA_trainedmodel

Predict using a MOA classifier, MOA regressor or MOA recommender on a new dataset

MOA_recommender

Create a MOA recommendation engine