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MXM (version 0.7)

Discovering Multiple, Statistically-Equivalent Signatures

Description

Feature selection methods for identifying minimal, statistically-equivalent and equally-predictive feature subsets. The package name 'MXM' stands for "Mens eX Machina", meaning "Mind from the Machine" in Latin.

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Version

Install

install.packages('MXM')

Monthly Downloads

1,130

Version

0.7

License

GPL-2

Maintainer

Michail Tsagris

Last Published

March 4th, 2016

Functions in MXM (0.7)

censIndLR

Conditional independence test for survival data
MMPC.temporal.output-class

Class "MMPC.temporal.output"
MXM-package

This is an R package that currently implements feature selection methods for identifying minimal, statistically-equivalent and equally-predictive feature subsets. In addition, two algorithms for constructing the skeleton of a Bayesian network are included.
Constraint based feature selection algorithms

SES: Feature selection algorithm for identifying multiple minimal, statistically-equivalent and equally-predictive feature signatures. MMPC: Feature selection algorithm for identifying minimal feature subsets.
testIndZIP

Zero inflated Poisson regression conditional independence test for discrete (counts) class dependent variables
reg.fit

Regression modelling
testIndNB

Negative binomial regression conditional independence test for discrete (counts) dependent variables
testIndRQ

Quantile regression conditional independence test for continous class dependent variables
testIndBeta

Beta regression conditional independence test for proportions/percentage class dependent variables and mixed predictors
plota

Plot of an undirected graph
testIndMVreg

Linear regression conditional independence test for continous class multivariate target variables.
MMPCoutput-class

Class "MMPCoutput"
model

Regression model(s) obtained from SES
cv.ses

Cross-Validation for SES
SES.temporal.output-class

Class "SES.temporal.output"
Constraint based feature selection algorithms for longitudinal data

SES.temporal: Feature selection algorithm for identifying multiple minimal, statistically-equivalent and equally-predictive feature signatures. MMPC.temporal: Feature selection algorithm for identifying minimal feature subsets.
MXM-internal

Internal MXM Functions
ridge.plot

Ridge regression
testIndGLMM

Linear mixed models conditional independence test for longitudinal class variables
Skeleton of the PC algorithm

The skeleton of a Bayesian network produced by the PC algorithm
testIndSpearman

Spearman's conditional independence test for continuous class variables
testIndLogistic

Conditional independence test for binary, categorical or ordinal class variables
testIndPois

Poisson regression conditional independence test for discrete (counts) class dependent variables
nei

Returns and plots, if asked, the node(s) and their neighbour(s), if there are any.
ridge.reg

Ridge regression
CondIndTests

MXM Conditional Independence Tests
SESoutput-class

Class "SESoutput"
testIndReg

Linear regression conditional independence test for continous class variables
mmhc.skel

The skeleton of a Bayesian network produced by MMHC
gSquare

G square conditional independence test for discrete data
testIndFisher

Fisher's conditional independence test for continuous class variables
ridgereg.cv

Cross validation for the ridge regression