train.dbcsp: Training process of a dbcsp object, using LDA classifier.

In dbcsp: Distance-Based Common Spatial Patterns

Training process of a dbcsp object, using LDA classifier.

Description

This function applies DB-CSP to the instances and perform the training of a Linear Discriminant Analysis (LDA) classifier using the object data.

Usage

## S3 method for class 'dbcsp'
train(x, selected_q=x@q, fold=x@fold, seed=x@seed, verbose=TRUE,...)

Arguments

x	object of class dbcsp.
selected_q	integer value indicating the number of vectors to use when training the model, by default selected_q=x@q.
fold	integer value, by default fold=x@fold. It controls the number of partitions. If fold==1 a train/test split is performed, with p=0.2 for test indices.
seed	numeric value, by default fold=x@seed. Set a seed to ensure reproducible results.
verbose	logical
...	not currently used.

Value

The dbcsp object with the training results saved as list in x@out:

• vectors The projection vectors obtained after applying CSP.

• eig The eigenvalues obtained after applying CSP.

• proy The variance values of the projected signals obtained after applying CSP.

• acc The mean accuracy value obtained for training data applying cross validation.

• used_folds List of the folds used in the cross validation.

• folds_acc Accuracy values for each of the folds of the cross validation.

• model The trained LDA classifier.

• selected_q The number of vectors used when training.

See Also

dbcsp, print, summary, selectQ, predict, plot, boxplot

Examples

# Read data from 2 classes
x <- AR.data$come[1:20]
y <- AR.data$five[1:20]
mydbcsp <- new("dbcsp", X1 = x, X2 = y)
mydbcsp <- train(mydbcsp,fold=3)
print(mydbcsp@out$acc)

dbcsp documentation built on June 30, 2022, 5:05 p.m.