search for: undersample

...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(r...

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

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

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)?

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

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.

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.