Parsimonious models

Parsimonious models are simple models with great explanatory predictive power. They usually explain data with a minimum number of parameters, or predictor variables. MoEClust is the R package that fits finite Gaussian mixtures of experts' models. It uses a range of parsimonious covariance with the help of EM or CEM algorithms.

Follow these steps to create a range of parsimonious covariance models with our AirQualityUCI dataset:

  1. Install the package that is required to create a parsimonious model of our dataset:
> install.packages('devtools') Installing package into 'C:/Users/Radhika/Documents/R/win-library/3.5' (as 'lib' is unspecified) trying URL 'https://cran.rstudio.com/bin/windows/contrib/3.5/devtools_2.0.2.zip' Content ...

Get Hands-On Exploratory Data Analysis with R now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.