a dataset of samples from just cerebellum and hippocampus, two parts of the brain, and a predictor matrix with 10 randomly selected columns using the following code:

library(dslabs) library(caret) library(tidyverse) data("tissue_gene_expression") set.seed(1993) #if using R 3.6 or later set.seed(1993, sample.kind="Rounding") ind <- which(tissue_gene_expression$y %in% c("cerebellum", "hippocampus")) y <- droplevels(tissue_gene_expression$y[ind]) x <- tissue_gene_expression$x[ind, ] x <- x[, sample(ncol(x), 10)] 

Use thetrain()function to estimate the accuracy of LDA. For this question, use the version oftissue_gene_expressioncreated with the code above: do not split it into training and test sets (understand this can lead to overfitting). Report the accuracy from thetrain()results (do not make predictions).

What is the accuracy?