learnAlgo: Create an instance of the ['LearnAlgo'] class

In MixAll: Clustering and Classification using Model-Based Mixture Models

Description

There is two algorithms and two stopping rules possibles for a learning algorithm.

• Algorithms:

  • Impute Impute the missing values during the iterations

  • Simul Simulate the missing values during the iterations

• Stopping rules:

  • nbIteration Set the maximum number of iterations.

  • epsilon Set relative increase of the log-likelihood criterion.

• Default values are 200 nbIteration of Simul.

The epsilon value is not used when the algorithm is "Simul". It is worth noting that if there is no missing values, the method should be "Impute" and nbIteration should be set to 1!

Usage

learnAlgo(algo = "Simul", nbIteration = 200, epsilon = 1e-07)

Arguments

algo	character string with the estimation algorithm. Possible values are "Simul", "Impute". Default value is "Simul".
nbIteration	Integer defining the maximal number of iterations. Default value is 200.
epsilon	Real defining the epsilon value for the algorithm. Not used by the "Simul" algorithm. Default value is 1.e-7.

Value

a [LearnAlgo] object

Author(s)

Serge Iovleff

Examples

learnAlgo()
learnAlgo(algo="simul", nbIteration=50)
learnAlgo(algo="impute", epsilon = 1e-06)

MixAll documentation built on Sept. 7, 2019, 3 a.m.