Dear R-gurus,
Here is what I need to do..
I have two .txt files that are in a matrix form (each looks something like
this:
0.033482 0.02238 0.026677
0.034553 0.023226 0.028855
0.035017 0.023262 0.02941
0.036262 0.023306 0.029706
0.037252 0.024644 0.032053
)
I need to write a code such that it pulls these two matrices into a data
frame and then runs the LDA and compares the classification results of the
two stimuli against one another. I am not sure how to do that at all, but
here is what I have thus far (not sure about the syntax 100%)
# lda, nnet, prcomp, etc are in the MASS library
library(MASS)
# pull matrices (made by 3dmaskdump) into a data frame
#first file
L_heap_hoop_4 <-
data.frame(as.matrix(t(read.table(file="L_Heap_4_top_ten.txt")))*100000,syll
= c(rep("heap")) <~~~ NEED specification here
#second file
L_heap_hoop_4 <-
data.frame(as.matrix(t(read.table(file="L_Hoop_4_top_ten.txt")))*100000,syll
= c(rep("hoop")) <~~~ NEED specification here
# run the LDA and compare the clasification results of the two stimuli
against one another
table(lda(syll ~ ., L_heap_hoop_4, CV =TRUE)$class,$syll)
....
any input would be highly appreciated.
--
View this message in context:
http://n4.nabble.com/Linear-Discriminant-Analysis-in-R-tp998567p998567.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
