summary.mdr: Summarizing the results of an MDR model

In MDR: Detect gene-gene interactions using multifactor dimensionality reduction

Description

summary method for class 'mdr', after fitting with mdr.cv or mdr.3WS

Usage

## S3 method for class 'mdr'
summary(object,...)

Arguments

object	an object of class 'mdr', a result of a call to either mdr.cv or mdr.3WS
...	additional arguments

Value

a table, with columns for level of interaction, bests MDR models for each level (including overall best model), and accuracy results. Accuracy results depend on the validation method for object.

Level	level of interaction
Best Models	best MDR by level
Classification Accuracy	average classification accuracy (percent) calculated from the training sets; for mdr.cv
Prediction Accuracy	average prediction accuracy (percent) calculated from the testing sets; for mdr.cv
Cross-Validation Consistency	the number for times a model was chosen as 'best' out of k, for k-fold cross-validation; for mdr.cv
Training Accuracy	classification accuracy (percent) calculated from the training set; for mdr.3WS
Testing Accuracy	classification accuracy (percent) calculated from the testing set; for mdr.3WS
Validation Accuracy	classification accuracy (percent) calculated from the validation set; for mdr.3WS

...

Author(s)

Stacey Winham

See Also

mdr.cv, mdr.3WS, predict.mdr, plot.mdr

Examples

#load test data
data(mdr1) #consider a subset with the response and the first 10 predictors

fit1<-mdr.3WS(data=mdr1[,1:11],K=2) #fit mdr model with 3WS
summary(fit1) #summarizes results of the fit

fit2<-mdr.cv(data=mdr1[,1:11],K=2,cv=5) #fit mdr model with 5-fold CV
summary(fit2)

MDR documentation built on May 29, 2017, 7:05 p.m.