search for: undersampled

Displaying 7 results from an estimated 7 matches for "undersampled".

2006 Mar 13
1
Newbie error or bug?
...plingfreq <- 1000*2.5 aliasfreqin1msec = 2.5 drawingpoints = 10000 time = (0:drawingpoints)/drawingpoints signal = sin(freqin1msec*2*pi*(time)) alias = -sin(aliasfreqin1msec*2*pi*(time)) undersamplinginterval = max(time)/8 seq (0, max(time), by=undersamplinginterval) -> undersamplingtimes undersampled = sin(freqin1msec*2*pi*undersamplingtimes) plot(time,signal,type="l", col="blue", xaxs="r", yaxs="r", xlab="Time (msec)", ylab="Signal", main="Aliasing", sub="Sampling 5KHz source (blue) at 8KHz (dots) gives 2.5KHz alias(re...
2017 Jan 05
4
Regresión Logística desbalanceada
Hola Comunidad, Feliz Año 2017: Tengo un problemilla con una regresión logística desbalanceada, tengo demasiados TRUE (93%). ¿Sabría alguién alguna forma de corregir el problema con R? Un slaudo, Milagros Camacho --- El software de antivirus Avast ha analizado este correo electrónico en busca de virus. https://www.avast.com/antivirus
2010 Sep 27
1
smooth contour lines
Is there an easy way to control smoothness of the contour lines? In the plot I am working on due to the undersampling the contour lines I am getting are jugged, but it is clear "by eye" these should be basically straight lines. In maps package I found smooth.map function, but maybe there is a more generic way of accomplishing the same thing. Ideally there would be an option to control
2004 Mar 09
2
SVM unbalanced classes
Hi! I am using R 1.8.1 and the svm of the e1071 package for classification. The problem is that I have unbalanced classes e.g. the first one is much bigger than the second one and therfore the svm is biased to the first class. If I manually adjust the class size the bias disappears. The question is then how to include this unequal class distribution to the svm (e.g. via wheights or costs)?
2007 Feb 15
2
Does rpart package have some requirements on the original data set?
Hi, I am currently studying Decision Trees by using rpart package in R. I artificially created a data set which includes the dependant variable (y) and a few independent variables (x1, x2...). The dependant variable y only comprises 0 and 1. 90% of y are 1 and 10% of y are 0. When I apply rpart to it, there is no splitting at all. I am wondering whether this is because of the
2006 May 24
1
(PR#8877) predict.lm does not have a weights argument for
I am more than 'a little disappointed' that you expect a detailed explanation of the problems with your 'bug' report, especially as you did not provide any explanation yourself as to your reasoning (nor did you provide any credentials nor references). Note that 1) Your report did not make clear that this was only relevant to prediction intervals, which are not commonly used.
2000 Apr 12
2
Comparison Between MP3 and Vorbis
Hello All, I realize that I am using pre-release code. I realize that the bitstream format will change in a couple of days. I realize that at this point comparisons between MP3 and Vorbis still don't mean much. BUT I couldn't resist. I ripped a random track off of one of my CDs and did some comparisons between Vorbis and MP3. I thought you guys might be interested in the results.