Dearest all,
Objective: I am now learning neural networks. I want to see how well can
train an artificial neural network model to discriminate between the two
files I am attaching with this message.
http://r.789695.n4.nabble.com/file/n2240582/3dMaskDump.txt 3dMaskDump.txt
http://r.789695.n4.nab
Joris,
Thank you, I have corrected my mistakes. I very much appreciate your time
and patience.
All my best,
Cobbler.
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Hi Janis,
As you have suggested below is the output for the following:
test.vowel <- vowel_features[,1:10]
test.mask <- mask_features[,1:10]
dput(test.vowel)
dput(test.mask)
--- NOTE: outputs are limited
>>test_vowel first 12 columns are all zero (total of 26 columns)
V1 V2 V3
Thanks for being patient with me.
I guess my problem is with understand how grouping in this particular case
is used:
one of the sample codes I found online
(http://www.statmethods.net/advstats/discriminant.html)
library(MASS)
fit <- lda(G ~ x1 + x2 + x3, data=mydata, na.action="na.omit", CV=TRU
Joris,
You are a life saver. Based on two sample files above, I think lda should go
something like this:
vowel_features <- read.table(file = "mappings_for_vowels.txt")
mask_features <- data.frame(as.matrix(read.table(file =
"3dmaskdump_ICA_37_Combined.txt")))
G <- vowel_features[15]
cvc_lda <-
Dear R gurus,
Thank you all for continuous support and guidance -- learning without you
would not be efficient.
I have a question regarding LD analysis and how to best code it up in R.
I have a file of (V52 and 671 time points across all columns) and another
file of phonetic features (each vow
Dear all,
I have a file with 57 columns (671 time points in each column)
File looks like this:
10.279191 -1.203200e-02 -0.166772 6.12080e-02 0.196379
4.591900e-02 0.293689
20.267017 -1.150700e-02 -0.159463 5.85400e-02 0.187775
4.392200e-02 0.280854
30.053778 -2.
Dear R gurus,
We are working on a problem in R - the following script is getting a subset
of values from a table that is read in and calculating the average of these
values in the subset defined.
the table looks like this:
subject stim trial xmax ymax xmin ymin flag
1 4 dur1
Hello R gurus,
I am having difficulties running a chunk of code that I otherwise thought
was correct..
> if (lower < max(length(IC_peaks),length(IC_valleys))) {
+ valley_index <- IC_valleys[lower+1]
+ for (i in seq(peak_index,valley_index-1)) {
+ IC_peaks_and_valleys <- c(IC_peaks_and_valleys, "
I need to convert foo.txt file into as.matrix
.txt file is a single column of numbers
(i.e.
-0.303904
-0.889965
-0.0270313
-0.387125
0.189837
-0.14858
-0.651178
-0.162632
0.449309
)
and I need to find out the correct syntax to read in this table as.matrix
I tried as.matrix(rea
Hello,
I am pretty new to R. I am working on neural network classifiers and I am
feeding the nnet input from different regions of interest (fMRI data). The
script that I am using is this:
library (MASS)
heap_lda <-
data.frame(as.matrix(t(read.table(file="R_10_5runs_matrix9.txt")))*10,syll
=
Hello,
As a result of running linear discriminant analysis, I need to be able to
plot the resulting file. I am not sure what the best way to do this is. So
far I have tried regular plot("insert_file_name_here") command but the error
it gives me is Error in plot.new() : figure margins too large
h
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:
0.0334820.02238 0.026677
0.0345530.0232260.028855
0.0350170.0232620.02941
0.0362620.023306
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